Role Overview

We are looking for a Senior GenAI Engineer with strong hands-on experience in

building production-grade Generative AI solutions. The role requires deep

expertise in agentic AI architectures, LLM orchestration, and advanced RAG

pipelines, with proven experience in deploying scalable, enterprise-grade

solutions (not PoCs).

Key Responsibilities

 Design and build end-to-end production-grade GenAI applications using

LLMs

 Develop and orchestrate agentic AI systems (single agent & multi-agent)

for complex enterprise workflows

 Implement RAG pipelines including document ingestion, embeddings,

retrieval optimization, and response synthesis

 Build and optimize LLM orchestration workflows with strong focus on

latency, cost, and scalability

 Implement observability frameworks (tracing, monitoring, logging) for GenAI

systems

 Define and execute evaluation frameworks for LLM response quality,

grounding, and hallucination management

 Develop scalable backend services using Python + FastAPI

 Build lightweight UI layers using Streamlit for demos/internal tools

 Ensure production readiness including scalability, resilience, and fault

tolerance

 Collaborate with architecture, data, and platform teams to integrate GenAI into

enterprise ecosystems

Mandatory Skills (Strict – No Compromise)



– REJECT PROFILES IF ANY OF

THE BELOW MENTIONED IS MISSING

 Proven experience in building production-grade GenAI solutions (must

demonstrate real deployments)

 Hands-on expertise in agentic frameworks & orchestration:

o AWS AgentCore / Strand Agents

o LangGraph (or equivalent agent orchestration frameworks)

o Multi-agent system design

 Solid hands-on experience with RAG architectures:

o Vector DBs (FAISS, Pinecone, OpenSearch, Chroma, etc.)

o Embeddings & retrieval strategies (hybrid search, reranking,

grounding)

 Deep understanding of LLM orchestration workflows

 Experience in LLMOps / Observability / Evaluation:

o Monitoring LLM performance, tracing, logging

o Evaluation frameworks (RAGAS, DeepEval or equivalent)

 Strong coding expertise in Python

 Experience building APIs using FastAPI

Good-to-Have

 Experience with AWS Bedrock / SageMaker-based GenAI deployments

 Exposure to guardrails, prompt injection handling, and GenAI risk controls

 Knowledge of cost optimization & token efficiency strategies

 Experience in enterprise domains (BFSI, Pharma, Healthcare, Insurance)

 CI/CD and containerized deployment (Docker/Kubernetes)

Pay: ₹550,000.00 - ₹900,000.00 per year

Work Location: Remote

📌 Senior Engineer (India)
🏢 langma International
📍 India