Locations: Bangalore (Whitefield) / Pune (Talawade) / Chennai (Siruseri) / Mumbai (Airoli West)
Availability: Immediate candidates preferred

Role Overview:
This role will lead the design and implementation of an AI Factory platform to streamline development, deployment, monitoring and reuse of AI/ML & GenAI assets. The architect will define scalable MLOps + GenOps practices, build reusable components, standardize pipelines, and support cross-industry AI solutioning for pre-sales, PoCs, accelerators and delivery.

Key Responsibilities:

• Architect and build an AI Factory repository of reusable models, prompts, agents, APIs and accelerators

• Define and implement MLOps workflows (model development, deployment, CI/CD, governance)

• Design GenOps pipelines (prompt engineering, LLM orchestration, evaluation, optimization)

• Create blueprints/templates for standardized AI solution delivery across cloud platforms

• Build accelerators for common use cases (chatbots, doc intelligence, summarization)

• Support pre-sales, demos, RFP/RFI responses and technical strategy

• Work with data engineering, DevOps, cloud and security teams

Required Skills:

• Deep experience in MLOps tools: MLflow / Kubeflow / SageMaker / Azure ML / Vertex Pipelines

• Knowledge of GenOps frameworks: LangChain, LlamaIndex, Semantic Kernel, TruLens, Ragas

• Strong Python, YAML/JSON and API integrations

• Experience with CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps), Docker, Kubernetes

• Knowledge of model registries, observability, drift detection, auto retraining

• Ability to build architecture docs & PPT decks

Preferred Qualifications:

• Experience building an enterprise AI marketplace / model catalog

• Familiarity with LLMOps tools like W&B, PromptLayer, Arize AI

• Cloud certifications (AWS/Azure/GCP)

• Multi-cloud / hybrid AI deployment experience

Soft Skills:

• Strong leadership & mentoring

• Excellent communication & storytelling

• Innovation mindset and fast execution capability

• Comfortable in fast-paced, cross-functional environment