AWS AI Architect Location In office – 5 days work from office / Bangalore Experience Range 10 to 12 years Competency Area AWS AI / ML / GenAI Role Summary The AWS AI Architect will design enterprise AI, ML, and GenAI architectures using Bedrock, SageMaker, RAG, agentic AI, foundation models, and vector database patterns. Key Responsibilities Define AI / ML / GenAI architecture and reference patterns. Design RAG, model orchestration, evaluation, and integration approaches. Guide model selection, data readiness, security, and responsible AI principles. Lead discovery, solution planning, and architecture reviews. Provide technical leadership to AI leads and engineers. Specific Expertise Required Primary Skills Amazon Bedrock Amazon SageMaker AI architecture RAG Foundation models Model evaluation Ability to technically orient and handhold teams of 10-15 people Secondary Skills Vector databases LangChain / LlamaIndex MLOps Responsible AI guardrails Architecture governance Technical / Functional Skills Amazon Bedrock, SageMaker, foundation models, and AWS AI services RAG, embeddings, vector databases, and AI orchestration frameworks MLOps, model monitoring, guardrails, and evaluation approaches Architecture governance, security, and stakeholder consulting Preferred Certifications AWS Certified AI Practitioner AWS Certified Machine Learning Engineer - Associate AWS Certified Solutions Architect - Associate AWS Certified Solutions Architect - Professional Expected Deliverables AI / GenAI reference architecture Solution blueprint and architecture decisions Model evaluation and responsible AI guidance Implementation roadmap Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering, or related discipline Hands-on delivery experience aligned to the stated experience range and role scope Good to Have AWS certification or active AWS certification plan Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support

AWS Technical Lead Location In office 5 days’ work from office / Bangalore Experience Range 6 to 8 years Competency Area AWS Application team Role Summary The AWS Technical Lead will lead development teams, define coding and CI/CD practices, coordinate with architecture and DevOps teams, and ensure technical delivery quality. Key Responsibilities Lead developers through design, build, code reviews, testing, and release readiness. Define coding standards, branching practices, and CI/CD expectations. Coordinate with architects, DevOps, QA, security, and business stakeholders. Track technical risks, dependencies, and quality issues. Ensure components are secure, maintainable, and documented. Specific Expertise Required Primary Skills AWS application development Microservices REST APIs CI/CD Code reviews Agile delivery Secondary Skills Lambda API Gateway ECS / EKS DynamoDB / RDS Security standards Technical / Functional Skills AWS application development with Lambda, API Gateway, ECS / EKS or managed services Java, .NET, Node.js, Python or relevant enterprise stack REST APIs, microservices, and integration patterns CI/CD, Git, automated testing, and code quality practices Preferred Certifications AWS Certified Developer - Associate AWS Certified Solutions Architect - Associate AWS Certified DevOps Engineer - Professional Expected Deliverables Implementation plan Code review and quality records Release readiness checklist Technical risk tracker Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering or related discipline. Hands-on delivery experience aligned to the stated experience range and role scope. Good to Have AWS certification or active AWS certification plan. Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support.

AWS Gen AI Engineer Location In office 5 days work from office / Bangalore Experience Range 4 to 6 years Competency Area AWS AI / ML / GenAI Role Summary The AWS Gen AI Engineer will build AI-powered applications, RAG workflows, prompt frameworks, Bedrock integrations, and reusable GenAI accelerators. Key Responsibilities Build GenAI application components and integrations. Implement RAG pipelines, embeddings, and knowledge retrieval workflows. Develop prompts, evaluation logic, guardrails, and response quality checks. Integrate Amazon Bedrock and foundation models with business applications. Create reusable GenAI templates and accelerators. Specific Expertise Required Primary Skills Amazon Bedrock RAG Prompt engineering Python Embeddings Model evaluation Secondary Skills Vector stores Semantic search Lambda Step Functions API integration Technical / Functional Skills Amazon Bedrock, foundation models, embeddings, and RAG Prompt engineering, evaluation, guardrails, and response-quality checks Python, API development, Lambda, and Step Functions basics Vector stores, semantic search, and orchestration frameworks Preferred Certifications AWS Certified AI Practitioner AWS Certified Machine Learning Engineer - Associate AWS Certified Solutions Architect - Associate AWS Certified Developer - Associate Expected Deliverables GenAI application components RAG pipelines and prompt templates Evaluation and guardrail documentation Reusable GenAI accelerators Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering, or related discipline. Hands-on delivery experience aligned to the stated experience range and role scope. Good to Have AWS certification or active AWS certification plan. Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support.

AWS Data Lead Location In office - 5 days / Bangalore Experience Range 6 to 10 years Competency Area AWS Data & Analytics Role Summary The AWS Data Lead will lead the design and delivery of AWS data engineering and analytics solutions, guide data engineers and analytics engineers, and ensure that data platforms are scalable, secure, governed, reliable, and aligned to business outcomes. The role bridges architecture and hands-on delivery across data ingestion, transformation, storage, analytics, governance, operational readiness, and AI / GenAI data foundations. Job Role & Responsibilities Lead discovery sessions and translate business, analytics, and AI requirements into an executable AWS data platform backlog. Own technical delivery of data ingestion, ETL / ELT, data lake, warehouse, analytics, and streaming workstreams. Define solution standards for pipeline design, data modeling, coding, testing, orchestration, monitoring, and deployment. Guide and mentor data engineers and analytics engineers through design reviews, code reviews, and production-readiness checkpoints. Collaborate with the AWS Data Architect on target architecture, service selection, scalability, resilience, security, and cost optimization. Establish data quality rules, reconciliation controls, metadata, cataloging, lineage, and governance practices. Coordinate with AI / ML and GenAI teams to prepare trusted datasets, feature pipelines, knowledge repositories, and RAG-ready data assets. Manage technical risks, dependencies, defects, performance issues, and production incidents through root-cause analysis and corrective actions. Support estimations, proposals, proof-of-concepts, customer demonstrations, and reusable AWS data accelerators when required. Ensure documentation, knowledge transfer, and operational handover are complete for each release. Specific Expertise Required Should have worked on at least 1 project on AWS data migration. Should have AWS certification relevant to the role. Should be hands-on with ETL, Reporting, and Pipelines. Should be able to propose/use solutions, approaches, and required tools for AWS data migration. Required Primary Skills AWS data platform delivery using Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, and AWS Lake Formation. Strong SQL, Python, and PySpark skills for data ingestion, transformation, validation, and optimization. ETL / ELT pipeline design, data lake and lakehouse implementation, data warehousing, and dimensional modeling. Technical leadership for data engineering teams, solution reviews, sprint planning, and delivery governance. Data quality, metadata, lineage, cataloging, security, privacy, and access-control implementation. Secondary Skills Amazon EMR, Amazon Kinesis, AWS DMS, AWS DataSync, and Amazon OpenSearch. Streaming and event-driven data processing using Kinesis, Kafka, or equivalent technologies. Infrastructure as Code using Terraform or AWS CloudFormation and CI/CD for data workloads. Amazon QuickSight, Power BI, or Tableau integration for analytics consumption. AI / GenAI data foundations including feature stores, embeddings, vector-ready datasets, and RAG data pipelines. Technical / Functional Skills AWS services: Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, AWS Lake Formation, Amazon Kinesis, AWS DMS, AWS DataSync, and Amazon OpenSearch. Programming and data processing: SQL, Python, PySpark, Apache Spark, shell scripting, and Scala as an advantage. Data architecture: data lakes, lakehouse patterns, enterprise data warehouses, batch and streaming pipelines, CDC, data marts, and semantic layers. Databases: Amazon RDS, Aurora, DynamoDB, PostgreSQL, MySQL, and NoSQL platforms. Engineering practices: Git, CI/CD, automated testing, monitoring, logging, performance tuning, cost optimization, and operational support. Governance and security: IAM, encryption, Lake Formation permissions, data classification, lineage, auditability, and compliance controls. Preferred Certifications AWS Certified Data Engineer - Associate. Databricks Data Engineer certification or equivalent data-platform certification (desirable). Expected Deliverables AWS data solution design and delivery plan. Data ingestion, ETL / ELT, streaming, and orchestration pipelines. Curated data lake, lakehouse, warehouse, and analytics-ready datasets. Data models, interface specifications, mappings, and transformation rules. Data quality, reconciliation, lineage, security, and governance documentation. Code-review records, test evidence, performance tuning results, and release-readiness checklist. Monitoring dashboards, operational runbooks, incident RCA, and handover documentation. Reusable templates, reference patterns, accelerators, and lessons learned for the AWS competency. Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Data Engineering, Analytics, or a related discipline. 6 to 10 years of overall experience in data engineering or analytics, including hands-on AWS data-platform delivery and team leadership responsibilities. Demonstrated experience delivering production-grade data pipelines, data lakes, warehouses, or analytics platforms. Good to Have Experience with migration from on-premises, Azure, GCP, Hadoop, Snowflake, or legacy warehouse platforms to AWS. Exposure to AWS Well-Architected reviews, FinOps, data mesh, lakehouse, and domain-oriented data-product practices. Experience building data foundations for SageMaker, Bedrock, recommendation systems, predictive analytics, or GenAI / RAG use cases. Customer-facing consulting experience across discovery workshops, architecture reviews, estimations, proposals, and technical presentations. Experience creating competency assets such as reference architectures, playbooks, reusable frameworks, and proof-of-concepts.

AWS Data Architect Job Role & Responsibilities Define enterprise data platform architecture on AWS using Redshift, Glue, EMR, Athena, Lake Formation, and S3. Work on AWS data migration projects. Propose and utilize solutions, approaches, and required tools for AWS data migration. Orient and handhold teams of 10-15 people. Design AWS data lake, data warehouse, and analytics architectures. Define ingestion, transformation, governance, consumption, and security patterns. Guide data engineers and analytics engineers on implementation standards. Establish data quality, lineage, cataloging, and access control designs. Support workshops, architecture reviews, estimation, and solution governance. Specific Expertise Required Primary Skills Amazon Redshift AWS Glue Amazon S3 Athena Lake Formation Data architecture AWS Data migration ETL, Reporting Secondary Skills EMR Data modeling Data quality Power BI / QuickSight Data governance Technical / Functional Skills Redshift, Glue, EMR, Athena, Lake Formation, and S3 SQL, PySpark, Python, and distributed data processing concepts Data lake, data warehouse, and lakehouse architecture Data governance, cataloging, lineage, quality, and security Preferred Certifications AWS Certified Data Engineer - Associate AWS Certified Solutions Architect - Associate AWS Certified Solutions Architect - Professional Expected Deliverables Data platform reference architecture Logical and physical data architecture Data governance and security model Architecture review documentation Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering, or related discipline. Hands-on delivery experience aligned to the stated experience range and role scope. Good to Have AWS certification or active AWS certification plan. Any other cloud experiences will be an added advantage. Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support.

AWS Application Architect Job Role & Responsibilities Define AWS application architecture and design patterns. Design microservices, APIs, serverless, and event-driven architecture. Review security, reliability, scalability, and performance requirements. Guide modernization of legacy applications into AWS-native designs. Support technical leads and developers through design reviews. Manage a team of 10-15 people. Specific Expertise Required Primary Skills: AWS Lambda API Gateway Microservices REST APIs EventBridge ECS / EKS Secondary Skills: SQS / SNS Step Functions DynamoDB / RDS OAuth / IAM CI/CD design Technical / Functional Skills AWS Lambda, API Gateway, ECS / EKS, EventBridge, SQS, SNS, and Step Functions Microservices, REST APIs, serverless, and event-driven architecture Application modernization, domain decomposition, and integration patterns Security, resilience, performance, and observability design Preferred Certifications AWS Certified Developer - Associate AWS Certified Solutions Architect - Associate AWS Certified Solutions Architect - Professional Expected Deliverables Application architecture blueprint API and microservices design documents Modernization roadmap Architecture review records Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering, or related discipline. Hands-on delivery experience aligned to the stated experience range and role scope. Good to Have AWS certification or active AWS certification plan. Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support.

AWS AIML Engineer Location In office 5 days’ work from office / Bangalore Experience Range 2 to 5 years Competency Area AWS AI / ML / GenAI Role Summary The AWS AIML Engineer will develop predictive models, machine learning workflows, SageMaker / Bedrock solution components, and production-ready AI services. Key Responsibilities Develop ML models for prediction, classification, recommendation, and analytics use cases. Build feature engineering, training, evaluation, and deployment workflows. Implement SageMaker and Bedrock-based components. Deploy AI models and support monitoring and improvement. Collaborate with data, AI architecture, and application teams. Specific Expertise Required Primary Skills SageMaker Bedrock Python Feature engineering Model evaluation ML algorithms Secondary Skills PyTorch / TensorFlow / scikit-learn MLOps Model monitoring CI/CD basics Technical / Functional Skills Amazon SageMaker, Bedrock, feature engineering, and model deployment Python, scikit-learn, XGBoost, PyTorch, or TensorFlow SQL, data preparation, and model evaluation MLOps concepts, model monitoring, and CI/CD basics Preferred Certifications AWS Certified AI Practitioner AWS Certified Machine Learning Engineer - Associate AWS Certified Solutions Architect - Associate Expected Deliverables ML models and training pipelines Model evaluation reports Deployment and monitoring artifacts AI solution handover documentation Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering, or related discipline. Hands-on delivery experience aligned to the stated experience range and role scope. Good to Have AWS certification or active AWS certification plan. Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support.

AWS AI Lead Location In office 5 days Work from Office / Bangalore Experience Range 6 to 10 years Competency Area AWS AI / ML / GenAI Role Summary The AWS AI Lead will lead delivery of AI, ML, and GenAI use cases by coordinating engineers, reviewing solution quality, and aligning technical outcomes to business needs. Key Responsibilities Lead AI / ML / GenAI implementation squads. Translate business problems into AI use cases and implementation backlogs. Review models, prompts, RAG flows, evaluation, security, and observability. Coordinate across architects, data engineers, application teams, and business stakeholders. Coach engineers and contribute reusable AI patterns and accelerators. Specific Expertise Required Primary Skills Amazon Bedrock Amazon SageMaker RAG Prompt engineering Python Model evaluation LangChain / LlamaIndex API integration Secondary Skills Vector databases ML Ops Responsible AI guardrails Technical / Functional Skills Bedrock, SageMaker, and AWS AI service integration RAG, embeddings, vector databases, and foundation model concepts Python, APIs, model evaluation, and MLOps fundamentals Responsible AI, guardrails, security, and performance considerations Preferred Certifications AWS Certified AI Practitioner AWS Certified Machine Learning Engineer - Associate AWS Certified AI Solutions Architect - Associate Expected Deliverables AI solution design and technical backlog Model / prompt evaluation evidence Reusable AI patterns and accelerators Delivery and quality tracking Qualification B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering, or related discipline. Hands-on delivery experience aligned to the stated experience range and role scope. Good to Have AWS certification or active AWS certification plan. Experience in reusable assets, accelerators, cloud competency building, customer workshops, or proposal support.

Sales Executive Location: Noida, Sector 1 Work Mode: Onsite / Work from Office Experience: 1+ year in Sales Qualification: Graduate / Post Graduate; MBA in Marketing / International Business Role Overview We are looking for a dynamic and result-oriented Sales Executive to develop new markets, manage client relationships, and drive revenue growth, with a focus on international customers and distributors. Key Responsibilities Identify and develop new markets and prospective clients. Generate leads through online portals, trade fairs, exhibitions, networking, and other channels. Manage the end-to-end sales process, from prospecting and negotiation to order finalization. Build and maintain relationships with international buyers and distributors. Work towards monthly and annual sales targets. Analyse market trends, competitor activities, and customer requirements. Develop opportunities to expand business across existing and new markets. Required Skills & Experience Minimum 1 year of relevant sales experience. Graduate / Post Graduate qualification; MBA in Marketing / International Business. Strong communication, presentation, and negotiation skills. Ability to manage client relationships and drive business development. Working knowledge of MS Office and CRM tools. Result-oriented approach with a strong focus on achieving sales targets.

Director – Talent Acquisition Location: Cybercity, Gurgaon (5 Days from Office) Candidates from Gurgaon, Delhi (NCR) only will be preferred.Experience: 12+ Years in Executive Search / Recruitment Consulting Notice Period: Immediate to 30 Days Are you a seasoned executive search professional with a passion for building long-term client relationships and delivering exceptional leadership hiring solutions? We're looking for a Director – Executive Search to lead retained and exclusive search mandates while partnering with senior business leaders across a defined industry vertical. This is a high-impact, client-facing role for someone who thrives in a consultative, entrepreneurial environment. Key Responsibilities Lead end-to-end executive search and recruitment mandates for leadership and specialist hiring. Manage a portfolio of retained and exclusive search assignments while ensuring exceptional client delivery. Build trusted relationships with senior stakeholders through a consultative approach. Develop and execute strategic account plans to grow existing client partnerships. Drive business development by acquiring new clients and expanding existing accounts. Provide career advisory and a premium candidate experience throughout the recruitment lifecycle. Resolve complex client and candidate situations with professionalism and commercial acumen. Build a strong market presence through thought leadership, networking, and personal branding on LinkedIn and industry forums. Organize and lead webinars, roundtables, and networking events to strengthen market visibility. Maintain accurate candidate, client, and assignment data within recruitment CRM systems. Leverage recruitment analytics and market intelligence to optimize hiring strategies. Collaborate with global teams, sharing market insights and best practices. Mentor consultants and contribute to training and capability-building initiatives. What We're Looking For 12+ years of experience in 360° agency recruitment or executive search. Proven success delivering retained search and senior leadership hiring assignments. Strong business development and account management capabilities. Demonstrated ability to build and maintain long-term client relationships. Excellent stakeholder management, communication, and negotiation skills. Ability to manage multiple high-priority searches simultaneously. Strong networking skills with an established professional brand in your market. Experience using recruitment platforms such as LinkedIn Recruiter, Vincere, or similar ATS/CRM tools. Self-driven, commercially focused, and comfortable working in an autonomous, high-performance environment. Why Join Us? Opportunity to work on high-value executive search assignments. Entrepreneurial culture with significant autonomy and ownership. Exposure to global clients and cross-border search projects. Collaborative team focused on excellence and knowledge sharing. Clear opportunities to enhance your personal brand and career growth.