3 - 8 years

12 - 23 Lacs

Posted:8 hours ago| Platform: Foundit logo

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Skills Required

python for ai llm & genai agent development agentic frameworks (langgraph/autogen/crewai) cloud ai platforms (aws/azure/gcp) rag pipelines & vector search kubernetes & ci/cd deployment

Work Mode

On-site

Job Type

Full Time

Job Description

Senior AI Developer

You will work across multiple domainsincluding HR, finance, healthcare, and recruitmentdeveloping autonomous agents powered by LLMs, integrated tightly with enterprise systems.

As a senior team member, you will also mentor junior developers and contribute to capability building within the AI practice.

Key Responsibilities :

Build and deploy agentic applications using LLMs and agentic frameworks.

  • Design and develop

    MCP-compatible servers

    and integrate agents with enterprise systems (ERP, CRM, HCM).
  • Fine-tune LLMs and optimize agent workflows for reliability, cost efficiency, and performance.
  • Architect and implement

    agent evaluation pipelines

    , scoring functions, and test harnesses.
  • Conduct

    functional, regression, and adversarial testing

    for agent workflows.
  • Implement observability dashboards, monitoring, and feedback loops for agents.
  • Collaborate closely with product managers, data scientists, and business stakeholders.
  • Participate in demos, solution walkthroughs, and stakeholder engagements.
  • Mentor junior developers and contribute to

    internal AI capability building

    , best practices, and code reviews.

Mandatory Skills

  • Strong proficiency in

    Python

    for backend development and AI engineering.
  • Experience with

    agentic frameworks

    such as LangGraph, AutoGen, CrewAI, or similar.
  • Hands-on experience with

    cloud platforms

    and GenAI services:

AWS (Bedrock, Lambda, Cognito),

Azure, or

GCP.

  • Proven experience building

    AI/ML systems

    , including GenAI agents, RAG pipelines, vector search, and LLM orchestration.
  • Expertise with AI services such as

    AWS Bedrock, SageMaker, Inferentia

    ,

    Azure OpenAI

    , or

    Google Vertex AI

    .
  • Strong understanding of

    Docker, Kubernetes

    , and CI/CD pipelines for scalable deployment.
  • Knowledge of

    GDPR, CCPA

    , and responsible AI principles (fairness, bias mitigation, explainability).
  • Experience integrating AI systems with

    MCP servers

    , REST APIs, and enterprise data sources.
  • Data engineering experience, including:
  • Vector databases

    ,
  • Graph databases

    ,
  • Ingestion pipelines

    .
  • Experience in

    agent evaluation

    , scoring functions, and advanced debugging tools.

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