Job Description:-
Key Responsibilities
AI/LLM Engineering & RAG Systems
• Design and build end-to-end RAG pipelines (data ingestion embedding retrieval inference)
• Develop LLM-powered applications and multi-agent systems (ReAct, LangChain, LangGraph)
• Implement:
o Vector indexing & semantic search (Azure AI Search, VectorDBs)
o Hybrid retrieval (vector + keyword search)
o Prompt engineering and LLM orchestration
• Build automated evaluation frameworks (RAGAS, ROUGE, etc.) for model quality and performance
2. Backend & API Development
• Develop scalable microservices and APIs using Python (FastAPI/Flask preferred)
• Build services for:
o Data ingestion and normalization
o Embedding pipelines
o Inference orchestration
o Feedback and evaluation systems
• Integrate LLM services with enterprise data systems and APIs
3. Data Engineering & Pipelines
• Design and optimize pipelines using:
o Azure Data Factory, Azure Functions, Eve ntHub/Service Bus
o Data lakes, warehouses, and vector stores
• Handle:
o Structured + unstructured data ingestion
o Document processing, chunking, and metadata enrichment
• Implement secure data handling, PII masking, and governance controls
4. Azure AI & Cloud Engineering
• Build and deploy solutions using:
o Azure OpenAI / Azure AI Studio
o Azure Cognitive Search
o Azure ML / Databricks / Fabric
• Implement:
o Secure access (Azure AD, Managed Identity, Key Vault)
o Scalable distributed systems for inference workloads
5. MLOps, DevOps & Productionization
• Develop and maintain:
o CI/CD pipelines (Azure DevOps, GitHub Actions)
o Infrastructure as Code (Terraform)
• Implement:
o Model monitoring, evaluation, and retraining pipelines
o Performance tuning and load testing for LLM systems
• Containerization & orchestration using Docker/Kubernetes
6. Architecture & Technical Leadership
• Contribute to:
o Architecture diagrams (C4, sequence diagrams)
o API contracts and system design
• Provide technical guidance on:
o GenAI solution design patterns
o Agentic AI systems and orchestration strategies
• Collaborate cross-functionally with stakeholders and client teams
Required Skills & Experience
Core Technical Skills
• 6+ years of experience in AI/ML Engineering or Backend Development
• Strong Python expertise (FastAPI, ML/AI frameworks)
• Deep experience with:
o LLMs, Generative AI, NLP
o RAG architectures and vector databases
• Hands-on experience with:
o Azure AI stack (Azure OpenAI, Cognitive Search, AI Studio)
• Experience with:
o LangChain / LangGraph / Agent frameworks
o Embedding pipelines and semantic search
Systems & Engineering
• Strong understanding of:
o Distributed systems and microservices
o Event-driven architectures and async workflows
• Experience with:
o REST APIs, backend systems, and cloud-native design
o Databases (SQL, NoSQL, VectorDBs)
MLOps & Deployment
• Experience with:
o Model deployment, monitoring, and lifecycle management
o CI/CD and containerization (Docker/K8s)
• Familiarity with evaluation metrics for LLM systems (RAGAS, ROUGE, etc.)
Nice to Have
• Experience with:
o Multi-agent systems (ReAct, autonomous agents)
o Knowledge graphs / GraphRAG
o SharePoint Graph API & enterprise integrations
• Background in:
o Financial services, insurance, healthcare, or enterprise analytics
• Experience leading AI teams or large-scale projects
