Key Responsibilities:
- Lead architecture, design, and implementation of enterprise Generative AI solutions using Azure AI Services and Azure OpenAI.
- Design and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search systems.
- Drive end-to-end development of AI-powered applications including copilots, chatbots, and intelligent assistants.
- Collaborate with business stakeholders to identify GenAI use cases and translate them into scalable technical solutions.
- Define and enforce best practices for prompt engineering, model evaluation, governance, and responsible AI.
- Lead and mentor teams of AI engineers, developers, and data scientists.
- Design and develop scalable Python-based microservices and APIs for AI solutions.
- Ensure performance, scalability, reliability, cost optimization, and production readiness of AI systems.
- Establish MLOps pipelines, CI/CD workflows, and AI monitoring frameworks.
- Evaluate and adopt emerging AI technologies to improve business outcomes.
- Oversee deployment and production support of GenAI solutions.
- Ensure security, compliance, and responsible AI implementation standards.
- Participate in technical reviews, architecture decisions, and delivery planning.
Required Skills:
- 6–10 years of IT experience.
- Strong hands-on experience in Python development.
- Azure Cloud and Azure AI Services expertise.
- Azure OpenAI Service and Azure AI Studio experience.
- Strong understanding of LLMs and Generative AI systems.
- Hands-on experience building RAG-based solutions.
- Expertise in vector databases (Pinecone, FAISS, ChromaDB, Weaviate, etc.).
- Strong experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar frameworks.
- Prompt engineering, embeddings, and semantic search expertise.
- Microservices architecture and REST API development.
- CI/CD pipelines, Git, Azure DevOps, Docker, Kubernetes experience.
Preferred Skills:
- Experience leading AI/ML or GenAI engineering teams.
- Knowledge of AI governance, responsible AI, and model security.
- Experience with AI observability, fine-tuning, and evaluation frameworks.
- Exposure to MLOps platforms and production AI systems.
- Experience with multi-agent AI systems and orchestration frameworks.
- Strong stakeholder management and solution architecture experience.
Interview Focus Areas:
- Azure OpenAI and Azure AI Services
- Python system design and backend architecture
- LLM architecture and optimization strategies
- RAG pipeline design and enterprise-scale implementation
- Vector databases and embeddings
- LangChain / LlamaIndex / Semantic Kernel / CrewAI
- Prompt engineering and evaluation methods
- AI governance, security, and responsible AI
- MLOps, CI/CD, and deployment strategies
- Leadership, mentoring, and stakeholder management
Educational Qualification:
- Bachelor’s/Master’s in Computer Science, AI, Data Science, or related field
Location:
- Mumbai / Pune / Kochi / Chennai / Coimbatore / Hyderabad
Type: Onsite / Hybrid
Pay: ₹900,000.00 - ₹1,300,000.00 per year
Benefits:
Work Location: Hybrid remote in Pune, Maharashtra (Pune, Pune District)
