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Emplay

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Lead- AI Engineer

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Summary

Lead AI Engineer at Emplay designing and shipping production LLM-powered agents, RAG pipelines, and multi-agent orchestration on AWS. Day-to-day spans Python backend services (FastAPI/Flask), vector search (OpenSearch/Pinecone/pgvector), third-party CRM/API integrations, and owning CI/CD and cloud infrastructure reliability.

Compensation: ₹12L – ₹15L • No equity

Position: Lead- AI Engineer

Experience: 3-4 years

No of Position - 1

Location - Remote / Work from Home

Salary (CTC) - 12- 15 LPA

Role Overview

We are looking for a Lead- AI Engineer with hands-on experience in Generative AI, Retrieval-Augmented Generation (RAG), and AWS cloud services. You will work with teams to design and deliver production-grade LLM-powered features, build intelligent agents, and integrate enterprise tools — working closely with cross-functional teams to ship high-quality AI solutions at scale.

Key Responsibilities

  • Design, build, and deploy LLM-powered agents and conversational AI features on AWS.

  • Architect and optimise end-to-end RAG pipelines — embedding, vector indexing, and context retrieval.

  • Implement Model Context Protocol (MCP) servers to support multi-agent orchestration workflows.

  • Develop and maintain LLM evaluation frameworks for quality assurance and regression tracking.

  • Build scalable, multi-region cloud infrastructure leveraging core AWS services.

  • Secure APIs and enforce access controls, authentication flows, and data privacy standards.

  • Integrate third-party platforms (CRM, Sales Enablement, analytics tools) via REST APIs and webhooks.

  • Build bulk data ingestion/export pipelines and instrument usage analytics and logging.

  • Own CI/CD pipelines, automated regression testing, and production reliability.

  • Collaborate with product and engineering teams to scope, estimate, and deliver features on time.

Qualifications

  • 3-4 years of experience AI/ML engineering or a related technical role, preferably in SaaS or a cloud-native environment.

  • Hands-on experience with LLM APIs — AWS Bedrock, OpenAI, or Anthropic — and building production-ready GenAI features.

  • Strong knowledge of RAG pipeline design — embeddings, vector stores (OpenSearch, Pinecone, pgvector),and retrieval strategies.

  • Proficiency with agent frameworks such as LangChain or LlamaIndex; familiarity with MCP (Model ontext Protocol).Solid AWS skills — Lambda, ECS/EKS, S3, DynamoDB, OpenSearch, SQS, and multiregion architecture patterns.

  • Backend development in Python (FastAPI / Flask) — able to write and maintain production-quality services and APIs.

  • REST / GraphQL API design with OpenAPI documentation; experience with OAuth 2.0, SAML and OIDC.

  • Infrastructure-as-code experience using Terraform or AWS CDK; CI/CD pipelines with GitHub Actions or equivalent.

  • Strong problem-solving skills and ability to work with ambiguous requirements.

  • Good communication skills, able to work with both technical and non-technical stakeholders.

Preferred Skills

  • Experience with Sales Enablement or CRM integrations

  • Familiarity with advanced agent orchestration and multi-tool LLM workflows.

  • Prior experience in a B2B SaaS or enterprise software environment

Skills

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