SM Cloud Architect

Role Overview Our client is seeking an experienced Cloud Infrastructure Architect to lead the design and modernisation of secure, scalable and resilient cloud infrastructure across enterprise environments. The role involves defining cloud architecture, developing migration strategies, establishing infrastructure standards and optimising cloud operations across AWS, Microsoft Azure or Google Cloud. The successful candidate will collaborate with application, security, networking, DevOps and operations teams to deliver reliable and cost-effective cloud platforms aligned with business objectives. The ideal candidate will bring extensive experience in cloud infrastructure architecture, hybrid and multi-cloud environments, automation, disaster recovery, high availability and infrastructure governance. Key Roles & Responsibilities Define cloud infrastructure architecture, standards and technology roadmaps. Design scalable, secure and highly available cloud environments. Lead cloud migration, infrastructure modernisation and data centre transformation initiatives. Develop hybrid-cloud and multi-cloud architecture solutions where required. Design cloud networking, identity management, storage and compute infrastructure. Establish infrastructure-as-code and automated provisioning practices. Implement cloud security, compliance, resilience and disaster recovery controls. Drive infrastructure monitoring, observability and operational excellence. Optimise cloud costs, resource utilisation and infrastructure performance. Collaborate with application and DevOps teams to enable cloud-native delivery. Define backup, business continuity and high-availability strategies. Establish architecture governance, technical standards and reusable infrastructure patterns. Provide technical leadership and mentor cloud engineering teams. Preferred Qualifications Bachelor's or master's degree in Computer Science, IT or Engineering. 12–18+ years of IT infrastructure experience, including substantial cloud architecture experience. Proven experience designing and implementing enterprise cloud platforms. Strong knowledge of cloud networking, security, storage, compute and automation. Relevant AWS, Azure or Google Cloud architecture certifications preferred. Key Skills & Attributes Cloud architecture and infrastructure strategy. Hybrid-cloud and multi-cloud design. Infrastructure automation and standardisation. Cloud security and governance. High availability and disaster recovery. Cloud cost optimisation and capacity planning. Technical leadership and stakeholder management. Technical Skills AWS, Microsoft Azure or Google Cloud. Virtual networks, VPCs, load balancers and DNS. Compute, storage, backup and disaster recovery services. Terraform, CloudFormation or equivalent infrastructure-as-code tools. Docker and Kubernetes. CI/CD pipelines and DevOps practices. CloudWatch, Azure Monitor, Prometheus or equivalent monitoring tools. IAM, encryption, secrets management and security controls. Linux, Windows Server and enterprise networking. Reporting / Team Relationships Works closely with: CTO / Head of Infrastructure Enterprise Architecture Team Cloud Engineering and DevOps Teams Cybersecurity Team Application Development Teams IT Operations and Service Management Teams What the Role Offers This is a strategic technology leadership opportunity for a cloud professional who wants to shape the future of enterprise cloud infrastructure and digital transformation. The successful candidate will play an important role in designing secure, scalable and resilient cloud environments, driving infrastructure modernisation and developing integrated solutions across cloud engineering, security and operations. The role offers an opportunity to influence cloud strategy, lead architectural initiatives and contribute to the growth of a technology-driven organisation.

Ihre Chance Für ein international tätiges Unternehmen im Bereich kritischer Infrastruktur suchen wir einen erfahrenen Project Controller (m/w/d) für die DACH-Region. Unser Mandant investiert in den Neubau und die Erweiterung technisch anspruchsvoller Infrastrukturstandorte. Die Projekte zeichnen sich durch hohe Investitionsvolumina, komplexe Bau- und Technikleistungen sowie die Zusammenarbeit unterschiedlicher interner und externer Projektbeteiligter aus. In dieser Position übernehmen Sie eine zentrale Rolle bei der kaufmännischen Steuerung laufender Bau- und Erweiterungsprojekte. Sie sorgen für Transparenz hinsichtlich Budgets, Kostenentwicklungen und finanzieller Risiken und unterstützen das Projektmanagement dabei, Investitionsvorhaben wirtschaftlich und planmäßig umzusetzen. Besonders interessant ist die Position für Kandidaten aus dem Bauwesen, dem industriellen Anlagenbau, der technischen Gebäudeinfrastruktur oder vergleichbaren projektorientierten Branchen. Ihre Aufgaben Projektkostencontrolling: Überwachung und Steuerung der Projektkosten bei Neubau-, Erweiterungs- und Infrastrukturprojekten innerhalb der DACH-Region. Budgetüberwachung: Kontinuierliche Kontrolle von Projektbudgets, Kostenverpflichtungen, Bestellungen und tatsächlichen Ausgaben. Abweichungsanalysen: Identifikation, Analyse und Erläuterung von Kostenabweichungen sowie Ableitung geeigneter Handlungsempfehlungen. Forecasting und Reporting: Erstellung monatlicher Projektberichte, Kostenprognosen, Budgetübersichten und finanzieller Projektfortschrittsanalysen. Finanzielles Risikomanagement: Frühzeitige Erkennung von Kostenrisiken und Unterstützung der Projektverantwortlichen bei der Entwicklung geeigneter Gegenmaßnahmen. Projektadministration: Prüfung und Sicherstellung korrekter kaufmännischer Prozesse, insbesondere im Zusammenhang mit Bestellungen, Budgetfreigaben und Kostenbuchungen. Business Partnering: Enge Zusammenarbeit mit Projektleitern, technischen Planern, Bauverantwortlichen und dem Finanzbereich. Monatsabschluss: Unterstützung bei periodischen Abschlussarbeiten und der finanziellen Bewertung laufender Projekte. Prozessoptimierung: Mitwirkung an der Weiterentwicklung von Controlling-, Reporting- und Projektsteuerungsprozessen. Ihr Profil Abgeschlossenes Studium der Betriebswirtschaft, des Wirtschaftsingenieurwesens, des Bauingenieurwesens oder eine vergleichbare Qualifikation mit kaufmännischem Schwerpunkt. Mehrjährige Berufserfahrung im Projektcontrolling, Cost Controlling oder in der kaufmännischen Projektsteuerung. Erfahrung in der Kostensteuerung größerer Bau-, Investitions- oder Infrastrukturprojekte, beispielsweise im Hoch- und Industriebau, Anlagenbau, bei Produktionsstätten, Logistik- und Lagerimmobilien, technischen Gebäudeanlagen oder Rechenzentren. Fundierte Kenntnisse in der Budgetplanung, Kostenverfolgung, Abweichungsanalyse, Forecast-Erstellung und im finanziellen Projektreporting. Sicherer Umgang mit komplexen Projektbudgets, Bestellprozessen und finanziellen Projektverpflichtungen. Fähigkeit, wirtschaftliche Risiken frühzeitig zu erkennen, verständlich aufzubereiten und konkrete Handlungsempfehlungen abzuleiten. Erfahrung in der Zusammenarbeit mit technischen Projektleitern, Ingenieuren, Bauverantwortlichen und kaufmännischen Ansprechpartnern. Sehr gute Excel-Kenntnisse sowie Erfahrung im Umgang mit ERP-Systemen. Verhandlungssichere Deutsch- und Englischkenntnisse. Eine strukturierte, analytische und eigenständige Arbeitsweise sowie ausgeprägte Kommunikationsfähigkeit. Erfahrung mit Projekten innerhalb der DACH-Region ist von Vorteil. Was Sie erwartet Spannende Investitionsprojekte: Mitarbeit an anspruchsvollen Neubau- und Erweiterungsvorhaben im Bereich moderner, kritischer Infrastruktur. Internationales Umfeld: Zusammenarbeit mit interdisziplinären Projektteams und Ansprechpartnern innerhalb der DACH-Region. Gestaltungsspielraum: Möglichkeit, bestehende Controlling-Prozesse weiterzuentwickeln und eigene Ideen einzubringen. Flache Hierarchien: Direkte Kommunikationswege und eine offene, kollegiale Unternehmenskultur. Flexible Arbeitsgestaltung: Hybrides Arbeitsmodell mit flexiblen Arbeitsmöglichkeiten. Attraktive Zusatzleistungen: Betriebliche Altersvorsorge, Fahrradleasing und weitere Benefits. Langfristige Perspektive: Tätigkeit in einer zukunftsorientierten Branche mit kontinuierlichen Investitionen und Entwicklungsmöglichkeiten. Interesse geweckt? Sie verfügen über Erfahrung im Projektkostencontrolling größerer Bau- oder Infrastrukturvorhaben und möchten Ihre Expertise in einem internationalen, wachstumsorientierten Umfeld einbringen? Dann freuen wir uns auf Ihre Bewerbung. Als spezialisierte Personalberatung begleiten wir Sie vertraulich durch den gesamten Bewerbungsprozess und informieren Sie gerne in einem persönlichen Gespräch über unseren Mandanten sowie die Rahmenbedingungen der Position.

Role Overview Our client, a growing technology-driven organization, is looking for an experienced AI Architect to lead the design and implementation of enterprise AI solutions, including Generative AI, Large Language Models (LLMs), AI agents and intelligent automation. The role involves defining AI architecture, selecting appropriate technologies, integrating AI capabilities into enterprise applications and ensuring solutions are scalable, secure and commercially viable. The successful candidate will work closely with business stakeholders, data science teams, software engineers and cloud architects to translate business requirements into practical AI solutions. The ideal candidate will bring strong experience in enterprise architecture, machine learning, cloud-based AI platforms and emerging AI technologies, with the ability to drive AI adoption and innovation across business functions. Key Roles & Responsibilities Define enterprise AI architecture, technology strategy and implementation roadmaps. Design scalable AI and Generative AI solutions for complex business requirements. Architect LLM-based applications, Retrieval-Augmented Generation (RAG) and AI agent solutions. Evaluate AI models, frameworks, vector databases and orchestration technologies. Integrate AI capabilities with enterprise applications, APIs and data platforms. Design secure and scalable AI solutions across AWS, Azure or Google Cloud. Establish AI governance, responsible AI, data privacy and security standards. Optimise model performance, latency, accuracy and infrastructure costs. Collaborate with data scientists, software engineers, product owners and business teams. Lead AI proof of concepts, solution evaluations and production deployments. Define reusable AI components, reference architectures and engineering standards. Mentor technical teams and guide the adoption of emerging AI technologies. Preferred Qualifications Bachelor's or master's degree in Computer Science, AI, Data Science or a related field. 10–15+ years of overall technology experience, including relevant AI architecture experience. Strong experience designing and deploying enterprise AI or machine learning solutions. Hands-on exposure to Generative AI, LLMs and production AI applications. Experience with cloud-based AI platforms and enterprise integration patterns. Key Skills & Attributes Enterprise AI architecture and solution design. Generative AI, LLMs, RAG and AI agents. Machine learning and model deployment. API integration and distributed systems. AI security, governance and responsible AI. Stakeholder management and technical leadership. Strong analytical and problem-solving capabilities. Technical Skills Python and AI/ML frameworks. LangChain, LlamaIndex or equivalent frameworks. OpenAI models, Azure AI, AWS AI services or Google Cloud AI. Vector databases and embedding technologies. REST APIs, microservices and event-driven architecture. Docker, Kubernetes and CI/CD. MLflow, model monitoring and MLOps tools. Reporting / Team Relationships Works closely with: CTO / Head of Engineering Enterprise Architecture Team Data Science and AI Engineering Teams Cloud and Infrastructure Teams Product Management Team Information Security Team What the Role Offers This is a strategic leadership opportunity for an AI professional who wants to shape the future of enterprise AI, Generative AI and intelligent automation. The successful candidate will play an important role in developing scalable AI architectures, integrating intelligent solutions into business operations and driving innovation across enterprise technology platforms. The role offers an opportunity to influence AI strategy, lead architectural initiatives and contribute to the growth of a technology-driven organisation.

Talent Acquisition Manager Location: Zurich  SHAPE  \* MERGEFORMAT Sector: Industrial AI & Deep-Tech Level: Early career (1–4 years) The company Our Client is a fast-growing industrial AI scale-up in Zurich, building a world model for the next industrial revolution. Born out of leading Swiss academic AI research, its physics-grounded model predicts the next state of physical reality rather than the next word, and is already deployed with Fortune 500 manufacturers across discrete and process industries. Partnerships with several of the world's leading AI and technology companies are in place, and the company is heading into a significant seed round. Speed is the company's edge, and exceptional people are how it increases the pace. That is where you come in. The role As Talent Acquisition Manager, you guard the hiring bar. Every person you bring in should raise the level of the team, whether they are an underdog, a rising star or a proven performer. You will: Turn the product and research roadmap into a clear hiring plan, working with team leads across tech, research and strategy Design roles and offers that reflect company needs, market standards and start-up realities Find and test new channels every day to reach exceptional people, and double down on what works Run first interviews as two-way conversations, then write a clear yes or no with reasons Keep every candidate informed with fast, personal follow-up Own the hiring funnel tracker, measure conversion stage by stage and report it in Excel Run onboarding and offboarding, from contracts and access to a first-week plan Look after team morale and culture as the company grows Handle candidate and employee data, work-permit basics and salaries with care and discretion What you bring Early career experience in recruiting, HR or operations, ideally including screening and first interviews A track record you can show in numbers: hires made, stage conversion, time to hire Precision and discipline, from file formatting to funnel tracking Strong emotional intelligence and the drive to build a high-performing team Professional-level English; German is a plus Backgrounds that fit well include technical recruiters at deep-tech start-ups, agency recruiters or headhunters who have placed ML, software, robotics or hardware talent, recruiting coordinators, start-up People Operations generalists and Founders' Associates who have built a hiring process from scratch. Essential requirements EU/EFTA passport or a degree from a Swiss university Based in, or willing to relocate to, Zurich (fully on-site, no remote) Notice period of 3 months maximum Why apply You will shape the team behind a fast-rising European industrial AI company at a decisive stage, with real ownership from day one, direct work with the founders and a clear path to Chief of Staff. Contact Peter [email protected].

Operations Lead Industrial AI scale-up | Zurich, Switzerland | Fully onsite | Path to COO Our Client is one of Switzerland’s fastest-moving deep-tech companies. Born out of world-class research at a leading Swiss university, they have built a physics-grounded AI “world model” for manufacturing: a single foundation model that predicts what happens next on the factory floor, from machine failures and quality issues to energy use and robotic tasks. In under a year, the technology has gone live with Fortune 500 manufacturers, earned partnerships with some of the world’s leading technology companies and attracted strong investor backing. The team is growing quickly, and they need someone to make sure speed never turns into chaos. The opportunity As Operations Lead, you will be the CEO’s right hand and the operating system of the company. You will take everything operational off the team’s plate, spot problems before they surface, and close them before anyone else notices. Do it well, and you grow into the COO role. What you will do • Run administration, procurement, expense control, contracts and insurance, getting the best value on hardware, robots and licences • Coordinate external stakeholders on live projects: industrial partners, research institutions, suppliers and robot deliveries • Own onboarding, offboarding, team events and the rituals that keep a high-performing team energised • Build lean, agile processes and automate what repeats (n8n, Zapier, Power Automate or similar) • Manage the founders’ time and priorities, and handle confidential information with complete discretion What you will bring • 1–4 years in a demanding operational environment, in any sector: startups, aviation, logistics, events, luxury hospitality, consulting or as right hand to a founder or principal • A zero-defect mindset: every document, spreadsheet, number and deadline right the first time • Strong Microsoft 365 skills; familiarity with automation tools and basic Python is a plus • Calm under pressure, a talent for reading people, and the confidence to challenge founders directly • Professional-level English; German is a plus Essential requirements • Swiss Natonality or EU/EFTA passport • Based in, or willing to relocate to, Zurich (fully onsite) Why join A rare seat beside the founders of a company with genuine global ambition, real ownership from day one, and a clear path to COO as the business scales. Contact Peter WhartonAntal International, [email protected]

Job: Product Engineer Location: Amman, Jordan (On-site) Industry: Tech Startup (AI) Engagement Details: Engagement: Direct independent contractor Work setup: On-site in Amman, Jordan, six working days per week with one day off Compensation: JOD 2,000 to 4,000 gross base per month Benefits: Highest-tier GIG health insurance after probation and standard paid leave in Jordan About the Role:Our client, a YC-backed AI startup, is hiring a Product Engineer to take full ownership of the product lifecycle, from identifying opportunities and engaging directly with users to delivering production-ready features. This is a full-stack ownership role on AI customer experience infrastructure used by enterprises at scale across Europe, the US, and the GCC. Key Responsibilities: Identify Product Opportunities: Proactively identify gaps and areas for improvement, and bring proposals rather than execution alone Engage Directly with Users: Understand problems first-hand by speaking with the people experiencing them Deliver Features End-to-End: Plan, prioritize, and implement full-stack features using React, TypeScript, and Node.js from concept to production Own Quality: Take ownership of code reviews, testing, performance, and reliability Collaborate Closely: Work with the Customer Engineering team to incorporate real user feedback into future development Requirements: 3+ years of experience building and shipping software products Strong TypeScript, React, and Node.js skills, with the ability to own full-stack features independently Strong product sense, with the ability to identify opportunities for improvement and propose solutions Ability to deliver quickly without compromising code quality English fluency and strong written and spoken communication are non-negotiable Comfortable working directly with customers and prioritizing based on their feedback **Final engagement is conditional on an acceptable criminal-record check, including a certificate of non-conviction or equivalent, completed with the candidate's consent and in accordance with applicable law

Job: Customer Engineer Location: Amman, Jordan (On-site) Industry: Tech Startup (AI) Engagement Details: Engagement: Direct independent contractor Work setup: On-site in Amman, Jordan, six working days per week with one day off Compensation: JOD 1,800 to 2,800 gross base per month Benefits: Highest-tier GIG health insurance after probation and standard paid leave in Jordan About the Role:Our client, a YC-backed AI startup, is hiring a Customer Engineer to serve as the direct technical bridge between enterprise customers and the product. This is a hands-on engineering role with heavy customer exposure. Key Responsibilities: Primary Technical Point of Contact: Respond fast to customer queries, join video calls, and own resolution end-to-end Lead Technical Onboarding: Guide enterprise customers through setup, configuration, and integration with tools like Zendesk, Intercom, HubSpot, and others Debug & Troubleshoot: Diagnose and resolve complex issues in live customer environments Ship Code: Implement fixes, integration enhancements, and small features directly in the Node.js / TypeScript codebase Collaborate with Product Engineering: Share customer context, escalate systemic problems, and help prioritize what the team builds next Develop Platform Expertise: Build deep knowledge of the AI agents and prompt engineering to effectively advise customers on optimizing their support operations Document & Scale Knowledge: Document recurring issues, solutions, and integration patterns to strengthen internal knowledge and customer resources Requirements: 2-3+ years of strong software engineering experience with Node.js and TypeScript, writing and shipping production code Hands-on experience with AI agents and prompt engineering (core to the role) Previous customer-facing technical work: onboarding, debugging integrations, or similar in a SaaS environment Good understanding of (or fast ability to learn) helpdesk APIs: Zendesk, Intercom, HubSpot, etc. English fluency and strong written and spoken communication are non-negotiable, including clear writing and confident speaking on video calls with enterprise stakeholders Ability to operate effectively in a fast-moving startup: speed, customer impact, and getting things done Able to work with customers across US, EU, MENA and GCC time zones **Final engagement is conditional on an acceptable criminal-record check, including a certificate of non-conviction or equivalent, completed with the candidate's consent and in accordance with applicable law

Solutions Architect (Kubernetes)Abu Dhabi, UAE • Full-time Our client is one of the largest digital transformation companies in the region, delivering large-scale technology, infrastructure and managed services programs across the UAE and wider MENA market. Job Title: Solution Architect (Kubernetes)Location: Abu Dhabi, UAE (on-site)Employment Type: Full-timeReports To: Technical Solution Director Key Competencies Kubernetes Administration & Troubleshooting Container Management & Deployment Docker / Container Technologies Application Implementation & Deployment Production & Technical Support Incident & Problem Management Root Cause Analysis Python Scripting & Automation PowerShell Scripting & Automation Linux & Windows Administration Application Monitoring & Troubleshooting Kubernetes Networking CI/CD & DevOps Practices Helm & Kubernetes Package Management Log Analysis & Performance Monitoring Infrastructure Troubleshooting Automation & Process Improvement Required Technical Skills Strong understanding of Kubernetes architecture and components. Hands-on experience with containers and Docker/container technologies. Experience deploying and troubleshooting containerized applications. Good knowledge of Kubernetes objects: Pods, Deployments, Services, ConfigMaps, Secrets, Ingress, Namespaces, StatefulSets. Hands-on experience with Python scripting and automation. Good understanding of Linux and Windows operating systems. Experience with command-line troubleshooting and log analysis. Familiarity with Git and basic CI/CD concepts is preferred. Preferred Skills Experience with Kubernetes platforms such as AKS, EKS, or OpenShift. Knowledge of Helm and Kubernetes package management. Experience with CI/CD tools and deployment pipelines. Familiarity with monitoring and logging tools. Knowledge of cloud platforms such as Azure or AWS. Understanding of DevOps practices and Agile methodologies. Experience working in an ITIL-based support environment. Kubernetes & Container Implementation Deploy, configure, and maintain Kubernetes clusters and workloads. Implement and support Kubernetes resources such as Pods, Deployments, Services, ConfigMaps, Secrets, Ingress, and namespaces. Troubleshoot pod failures, CrashLoopBackOff, image-pull issues, resource constraints, and deployment failures. Support containerized applications using Docker/container technologies. Build, configure, and troubleshoot container images and container deployments. Assist with application onboarding and migration to Kubernetes/container platforms. Support upgrades, configuration changes, scaling, and optimization of Kubernetes environments. Implement health checks, resource limits, autoscaling, and appropriate deployment configurations. Python Automation Develop and maintain Python scripts to automate operational and support activities. Automate repetitive troubleshooting, monitoring, reporting, and deployment tasks. Create scripts for log analysis, system checks, health checks, and operational workflows. Troubleshoot and enhance existing Python-based automation tools. Integrate scripts with APIs and cloud/container platforms where required. PowerShell Develop and maintain PowerShell scripts for Windows administration and automation. Automate system administration, monitoring, configuration, and support tasks. Troubleshoot Windows-based application and infrastructure issues. Create PowerShell scripts for deployment, health checks, log collection, and operational activities.

Solutions Architect (Cloud)Abu Dhabi, UAE • Full-time Our client is one of the largest digital transformation companies in the region, delivering large-scale technology, infrastructure and managed services programs across the UAE and wider MENA market. Job Title: Solution Architect (Cloud)Location: Abu Dhabi, UAE (on-site)Employment Type: Full-timeReports To: Technical Solution Director Key Competencies Cloud Infrastructure Microsoft Azure Amazon Web Services (AWS) Cloud Networking Infrastructure as Code (IaC) Terraform Technical Support Cloud Implementation Incident & Problem Management Network Troubleshooting Automation Required Skills Hands-on experience with Microsoft Azure and/or AWS. Strong understanding of Cloud Networking concepts. Practical experience with Terraform and Infrastructure as Code (IaC). Practical experience with Infoblox. Experience troubleshooting cloud infrastructure and networking issues. Strong analytical, troubleshooting, and problem-solving skills. Good communication and customer-facing skills. Preferred Qualifications Azure or AWS certification such as Azure Administrator, Azure Network Engineer, AWS Solutions Architect, or AWS SysOps Administrator. Terraform certification or demonstrated hands-on Terraform experience. Experience with cloud migration or hybrid-cloud environments. Hands-on experience with Infoblox. Familiarity with monitoring and logging platforms. Knowledge of scripting using PowerShell, Bash, or Python. Experience working in ITIL/service-management environments. Cloud Implementation Implement and configure cloud infrastructure across Microsoft Azure and AWS. Provision and manage cloud resources including virtual networks, subnets, security groups, compute, storage, load balancers, and identity/access components. Participate in cloud migration, deployment, and infrastructure modernization projects. Support implementation activities from requirements gathering and design through deployment and handover. Validate cloud environments against security, performance, availability, and operational requirements. Cloud Networking Configure and troubleshoot cloud networking components across Azure and AWS. Work with VPC/VNet, subnets, routing tables, NAT, VPN, peering, private endpoints, DNS, and load balancing. Troubleshoot hybrid connectivity between on-premises infrastructure and cloud environments. Support network security controls, firewall rules, access policies, and network segmentation. Infrastructure as Code / Terraform Develop and maintain Terraform configurations for cloud infrastructure deployment. Use Infrastructure as Code (IaC) principles to automate and standardize cloud provisioning. Maintain reusable Terraform modules and infrastructure templates. Perform Terraform plan, deployment, troubleshooting, and state management activities. Follow version-control and change-management practices for infrastructure automation. AWS & Azure Operations Support day-to-day operations of AWS and Azure cloud environments. Troubleshoot cloud service availability, performance, connectivity, and configuration issues. Assist with cloud security, identity, monitoring, backup, and disaster-recovery activities. Identify opportunities to improve cloud reliability, scalability, automation, and cost efficiency.

Job Title: Senior Data Scientist – Machine Learning & GenAI - USA Industry: Data Science / Machine Learning / Generative AI Location: Houston, Texas, USA Salary: USD 125,000–150,000 per annum per annum + Benefits Work Authorization: US Citizens, Green Card holders and candidates with valid H-1B status About the Role We are seeking an experienced Senior Data Scientist – Machine Learning & GenAI with a strong foundation in traditional machine learning and data science, complemented by hands-on experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and agentic AI workflows. This is a highly applied role requiring someone who has built and implemented data science and AI solutions in real-world commercial or enterprise environments. We are particularly interested in candidates who combine strong technical capability with the confidence to engage directly with customers and work effectively across product and engineering teams. The successful candidate should not be purely academic or research-focused. Practical implementation experience, commercial awareness and strong communication skills are essential. Key Responsibilities Design, develop and deploy machine learning and statistical models to solve complex business problems. Develop practical Generative AI and LLM-based solutions, including RAG architectures and agentic AI workflows. Analyse large and complex datasets to identify trends, patterns and actionable business insights. Build predictive and analytical models that support product development and data-driven decision-making. Work closely with product managers, engineers and other stakeholders to integrate machine learning and GenAI capabilities into enterprise products and services. Translate customer and business requirements into scalable data science and AI solutions. Participate confidently in customer-facing discussions, communicating technical concepts, findings and recommendations to both technical and non-technical audiences. Evaluate and improve model performance, reliability and business impact. Provide guidance and mentorship to junior data scientists where appropriate. Keep abreast of developments in machine learning, Generative AI, LLMs and related technologies. Required Experience & Skills 7–15 years of relevant professional experience in data science, machine learning or a closely related discipline. Strong hands-on experience with traditional machine learning algorithms, predictive modelling and statistical techniques. Practical experience developing and implementing Generative AI and LLM-based applications. Hands-on knowledge of Retrieval-Augmented Generation (RAG) architectures and implementation. Experience with agentic AI or agent-based workflows. Strong proficiency in Python and/or R, including relevant data manipulation and machine learning libraries. Experience with frameworks such as Scikit-learn, PyTorch and/or TensorFlow. Strong SQL skills and experience working with large datasets. Experience with big-data technologies such as Spark, Hadoop or comparable platforms. Experience taking machine learning or AI solutions beyond experimentation into practical implementation or production. Strong analytical and problem-solving capabilities. Excellent written and verbal communication skills. Ability to engage confidently with customers and explain complex technical concepts to non-technical stakeholders. Proven ability to collaborate effectively with engineering, product and business teams. Preferred Qualifications Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Engineering or another relevant quantitative discipline. Experience developing data science or AI capabilities for enterprise products or platforms. Experience deploying ML and GenAI solutions into production environments. Familiarity with cloud platforms such as AWS, Microsoft Azure or Google Cloud Platform. Experience with data visualisation or business intelligence tools such as Tableau or Power BI. Previous customer-facing, consulting or product-oriented experience. Experience mentoring or technically guiding junior data scientists. What We Are Looking For The ideal candidate will combine three important dimensions: Strong Machine Learning FoundationYou should have substantial experience in traditional data science, statistical modelling, predictive analytics and machine learning. GenAI experience alone will not be sufficient. Practical GenAI CapabilityYou should be able to demonstrate hands-on experience building or implementing LLM applications, RAG solutions and/or agentic AI workflows for genuine business use cases. Commercial & Customer EngagementYou should be comfortable working beyond the technical environment, engaging with customers, understanding business requirements and explaining sophisticated AI and data science solutions clearly. Candidates should ideally be able to discuss specific examples of models or AI solutions they have developed, how these were implemented, the business problem addressed and the resulting impact. Working Environment You will work within a collaborative, product-focused environment alongside data scientists, engineers, analysts and product professionals developing innovative AI and data-driven solutions for enterprise customers. The environment places a strong emphasis on practical implementation, collaboration, continuous learning and measurable business outcomes, providing an opportunity to work at the intersection of established machine learning techniques and emerging Generative AI technologies.