Job Title: Senior GenAI Architect / Lead Agentic AI & LLM Platforms

Location: Chennai

Experience: 8+ years (with 3+ years in GenAI/LLM ecosystems)

Role Overview

- We are looking for a highly experienced, hands-on GenAI Architect/Lead to drive enterprise-wide adoption of Generative AI and building Agentic AI solutions. This role combines deep technical expertise, solution architecture to enable GenAI-led transformation across the SDLC and business workflows.
- You will work closely with engineering teams, architects, product owners, and leadership to design and implement scalable, production-grade GenAI systems, while also acting as a thought leader and change agent for GenAI adoption.

Key Responsibilities Technical Leadership & Delivery
- Lead a team of GenAI developers and backend engineers to deliver enterprise GenAI applications and accelerators.
- Translate business requirements into technical designs, work breakdown, implementation plans, and engineering tasks.
- Review architecture, code, prompt design, RAG pipeline design, data model, API design, and integration approaches.
- Ensure quality, performance, security, maintainability, observability, cost efficiency, and production readiness.

Advanced RAG, Semantic Search & Knowledge Architecture
- Design and optimize RAG pipelines including ingestion, chunking, metadata extraction, embeddings, vector indexing, hybrid retrieval, re-ranking, citation generation, and answer synthesis.
- Implement semantic search across structured, semi-structured, and unstructured knowledge sources.
- Integrate with enterprise knowledge repositories such as SharePoint, Confluence, S3, Google Drive, databases, ITSM tools, and document management systems.
- Define knowledge freshness, access-controlled retrieval, lineage, deduplication, feedback loops, and retrieval quality improvement mechanisms.

Agentic AI & MCP-based Tool Integration
- Design and implement agentic workflows using LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or equivalent.
- Implement tool calling, memory, workflow state, human-in-the-loop approval, API actions, and secure execution boundaries.
- Build or guide MCP server implementations for secure agent-to-tool and LLM-to-enterprise-system integration.
- Evaluate A2A communication patterns for multi-agent collaboration, delegation,



and hand-offs where relevant.

Backend, API, Data & Event-Driven Engineering
- Build scalable services using Python, FastAPI, Node.js, Java, or similar technologies.
- Design REST APIs and microservices for LLM orchestration, semantic search, ingestion, agent execution, feedback, and evaluation.
- Use SQL and NoSQL databases for application metadata, session history, audit logs, feedback, configurations, and workflow state.
- Design Redis caching patterns for session state, memory, rate limiting, token optimization, retrieval caching, distributed locks, and workflow continuity.
- Design asynchronous workflows using Kafka, RabbitMQ, Azure Service Bus, AWS SQS/SNS, Google Pub/Sub, or equivalent, including retry, DLQ, idempotency, ordering, and schema management.

Evaluation, Observability, Security & Governance
- Implement LLM tracing, prompt/version tracking, token usage monitoring, latency tracking, cost monitoring, and feedback analytics.
- Define evaluation datasets and metrics for faithfulness, groundedness, answer relevance, context relevance, hallucination rate, toxicity, latency, and cost.
- Use LangSmith, Langfuse, RAGAS, DeepEval, TruLens, Promptfoo, OpenTelemetry, Grafana, Prometheus, ELK, Datadog, or equivalent.
- Implement guardrails against prompt injection, jailbreaks, data leakage, unauthorized tool execution, toxic responses, and privacy violations.
- Support AI-assisted SDLC adoption using GitHub Copilot, Codex, CursorAI, Claude Code, Cline, or similar tools.

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Required Skills

- Enterprise GenAI Architecture (Expert)
- Design and implementation of GenAI reference architectures

- Platform strategy and governance

- Reusable accelerators and frameworks
- Non-Functional Requirements (NFRs)
- Enterprise-scale AI solution design
- RAG & Semantic Search (Expert)

- Hybrid Search





- BM25 Search

- Vector Databases

- Embeddings
- Re-ranking

- Citations and Grounding

- Agentic AI (Expert)

- LangGraph

- LangChain

- CrewAI

- AutoGen
- Multi-agent systems

- Planning and memory management
- Human-in-the-loop workflows
- MCP & A2A (Architect-Level Expertise)

- Model Context Protocol (MCP)

- MCP Servers and Gateways

- Tool Ecosystem Integration

- Secure Tool Execution
- Agent-to-Agent (A2A) Communication Patterns
- Multi-Agent Orchestration
- Backend APIs (Strong Hands-on)

- Python

- FastAPI
- Node.js

- Java

- REST APIs

- Microservices Architecture

- OpenAPI

- API Gateway Design

- Observability (Expert)

- LangSmith

- Langfuse

- RAGAS

- DeepEval

- Promptfoo

- OpenTelemetry

- Grafana

- Prometheus
- ELK Stack or equivalent monitoring solutions

- Data Architecture (Expert)
- SQL & NoSQL Databases

- Vector Databases

- Object Storage

- Analytics Stores

- Metadata Management

- Data Lineage

- Audit and Compliance Tracking

- Caching (Expert)

- Redis

- Session Continuity

- Memory Management

- Rate Limiting

- Distributed Locks

- Retrieval Caching
- Messaging & Event Processing (Expert)

- Kafka

- RabbitMQ
- Event-Driven Architecture

- Dead Letter Queue (DLQ)

- Retry Mechanisms

- Idempotency Patterns

- Event Schema Management

- Asynchronous Workflows
- Cloud & Model Strategy (Expert)

- Azure OpenAI

- AWS Bedrock

- Google Vertex AI

- OpenAI

- Anthropic Claude

- Google Gemini

- Hugging Face

- Small Language Models (SLMs)
- LLMOps / MLOps / DevOps (Expert)

- Prompt and Model Versioning

- Model Evaluation Frameworks

- CI/CD Pipelines

- Docker

- Kubernetes

- Helm Charts

- Terraform

- Deployment Automation
- Security & Responsible AI (Expert)

- AI Guardrails

- Prompt Injection Prevention

- LLM Shielding

- Privacy and Compliance Controls

- Access Management

- Audit Logging

- Model Risk Management

- Responsible AI Governance

Soft Skills & Leadership
- Excellent communication and stakeholder management skills
- Proven ability to drive adoption and influence teams
- Strong problem-solving and architectural thinking
- Experience in mentoring teams and leading technical initiatives

📌 Senior GenAI Architect Agentic AI & LLM Platforms (Chennai)
🏢 PwC India
📍 Chennai