Description :

Job Title : Lead AI Architect.

Location : India - Pune.

Experience Required : 12+ years.

Job Summary :

We are seeking an experienced, hands-on AI Architect (12+ years) to lead technical delivery and client engagement for Agentic AI platforms.

The role owns end-to-end design, productionisation and operationalisation of LLM-based solutions (RAG, fine-tuning, model serving) on Azure, and will act as the technical face to the client while leading a cross-functional delivery team.

What Success Looks like :

- Deliver production Agentic AI features that meet SLA targets for latency, throughput and reliability.

- Reduce time-to-value for LLM integrations via repeatable patterns, MLOps pipelines and reusable components.

- Maintain model governance, explainability and security posture appropriate for sensitive data domains.

Key Responsibilities :

- Architect and build Agentic AI systems : orchestrate agents, action executors, retrieval layers, and feedback loops.

- Design and implement LLM solutions (RAG, retrieval chains, prompt engineering, fine-tuning/LoRA/P-tuning) for production use.

- Own model deployment, serving and scaling on Azure (Azure AI, Azure ML, AKS, container registries) and hybrid setups.

- Build MLOps & ModelOps pipelines : CI/CD for models and services, automated testing, monitoring, drift detection and rollbacks.

- Lead data pipelines for retrieval : vector stores, semantic search, indexing, embeddings, data privacy & access controls.

- Implement model explainability, confidence scoring, adversarial protections and prompt security (prompt injection mitigation).

- Define and enforce model governance : versioning, reproducibility, lineage, audit trails and compliance.

- Collaborate with product, data engineering, security, DevOps and UX to ensure integrated delivery and acceptance.

- Mentor and upskill engineers; conduct technical reviews and pair programming; recruit when required.

- Act as primary technical contact for clients : present designs, lead architecture reviews, and support RFP/interview processes.

Required Skills & Experience :

- 12+ years in software engineering/AI with demonstrable, hands-on production experience.

- Deep experience with LLMs and RAG architectures : retrieval design, vector DBs (Pinecone/Weaviate/Milvus), embeddings.

- Proven track record in fine-tuning/customising LLMs (LoRA, full-fine tune, instruction tuning) and prompt engineering.

- Strong Azure AI stack experience : Azure OpenAI/GPT, Azure ML, AKS, Azure Functions, KeyVault, Data Factory/Synapse.

- Expertise in Agentic frameworks and orchestration (LangChain, LangGraph, custom agent frameworks).

- Production MLOps/ModelOps : CI/CD for models, model registry, automated testing, monitoring (Prometheus/Grafana/ELK), drift detection.

- Backend engineering : Python, FastAPI, microservices, Docker, Kubernetes, gRPC/REST, event-driven architectures.

- Data engineering basics : SQL/NoSQL, ETL, schema design, data lineage and data privacy controls.

- Security & compliance : secrets management, access controls, vulnerability remediation, data encryption in transit & at rest.

Good-to-Have Skills :

- Experience with hybrid/multi-cloud deployments and avoiding provider lock-in.

- Familiarity with LangGraph, agentic safety patterns, and adversarial robustness testing.

- Prior exposure to financial data or private markets / regulated data handling.

- Experience with model explainability tools (SHAP, LIME, integrated gradients) and bias/fairness testing.

- Familiarity with Terraform/ARM for infra as code and GitOps workflows.