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Help Enterprises Improve Talent Performance W/o Overwhelming Their Employees with Content and Tools
  • B2B
  • Growth Stage
    Expanding market presence
  • Growing fast
    Showed strong hiring growth in the past month

Lead- AI Engineer

  • ₹12L – ₹15L • No equity
  • |Remote ()
  • |3 years of exp
  • |Full Time
Posted: 3 weeks ago
Hires remotely in
Remote Work Policy

Remote only

Company Location
Visa Sponsorship

Not Available

RelocationNot Allowed
Skills
Python
CRM
API
REST APIs
AWS/EC2/ELB/S3/DynamoDB
AWS Cloud Services
MCP
AWS
Customer Relationship Management (CRM)
GraphQL
RESTful API
AWS Lambda
CICD
APIs
CI/CD
EKS
AWS EKS
CICD Pipeline
FastAPI
Amazon EKS
CICD & DevOps
Elastic Kubernetes Service(EKS)
Generative AI
LLMs
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
LLMs, Langchain, Llama-Index, Huggingface
LLM Frameworks (Langchain, Claude, LLamaIndex) RAG Technologies Embedding Models Vect
RAGs, ChatGPT, Hugging Face, LangChain, LlamaIndex, Transformers, VectorDB
Model Context Protocol (MCP)
MCP (Model Context Protocol)

About the job

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

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