GenAI / Agentic AI Automation

Senior Associate Forward Deployment Engineer (GenAI / Agentic AI Automation)

GenAI & Agentic AI Engineering * * Forward Deployed Engineering

Experience : 5 to 9 years

Locations : Bangalore & Hyderabad

Job Summary : A senior engineer who owns AI solutions end to end inside a client’s environment, from a vague problem to a production-grade deployment. As the technical owner, you will scope, architect, build, and ship GenAI and agentic solutions, and set the approach for evaluation and responsible AI.

Key Responsibilities

• Own AI solutions end to end, from discovery to a production-grade deployment on client infrastructure.
• Design agentic architectures and RAG pipelines that hold up at enterprise scale.
• Define the approach to prompt engineering, model evaluation, and responsible AI.
• Integrate solutions into enterprise systems and both structured and unstructured data.
• Make architecture, technology-selection, and design-review decisions.
• Work across the full stack to ship end to end.
• Mentor engineers and raise delivery capability.
• Codify reusable patterns and share field intelligence with the practice.

Required Qualifications

• Substantial software engineering experience with strong hands-on GenAI/agentic work in production.
• Deep experience with LLMs on AWS Bedrock and provider APIs, and with agent frameworks.
• Experience designing and deploying enterprise AI applications (agentic workflows, RAG, vector databases, embeddings, semantic search).
• A solid handle on prompt engineering, model evaluation, and responsible AI in production.
• Strong full-stack engineering (Python and TypeScript, APIs) and data engineering fundamentals.
• Ability to navigate ambiguity and drive outcomes at pace.

Preferred Qualifications

• AWS AI services (Bedrock, SageMaker).
• Enterprise AI platforms (Palantir Foundry/AIP, Databricks, Snowflake Cortex).
• Production deployment (Docker, Kubernetes, CI/CD, Terraform).
• Experience in regulated industries.
• A track record as an early engineer or technical founder building from zero to production.
• AWS Certified Solutions Architect Professional; an AI/ML certification such as AWS Certified Machine Learning – Specialty.

Technical Skills & Tools

• LLMs & AI: AWS Bedrock, Anthropic Claude, OpenAI; prompt engineering, model evaluation, responsible AI
• Agent frameworks & orchestration: LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen; workflow orchestration
• Retrieval & RAG: embeddings, vector databases (Pinecone, pgvector, Weaviate, Qdrant, OpenSearch), semantic search, rerankers
• Evaluation & observability: evaluation harnesses, Langfuse, OpenTelemetry
• Languages: Python, TypeScript / JavaScript
• Backend & APIs: FastAPI, Node.js, microservices, REST, GraphQL
• Frontend: React, TypeScript
• Data: SQL / NoSQL, data pipelines, streaming (Kafka, Kinesis), structured and unstructured data
• Good to have: AWS SageMaker, Docker, Kubernetes, CI/CD, Terraform, Databricks, Snowflake, Palantir Foundry