Platform Engineer III

• *Job Summary**
• --------------

We are seeking a highly motivated GenAI / Agentic AI Developer to join our AI Engineering team and build next\-generation AI\-powered solutions. The ideal candidate will have hands\-on experience developing applications using Large Language Models (LLMs), Agentic AI frameworks, Retrieval\-Augmented Generation (RAG), and enterprise AI platforms. This role involves designing, developing, and deploying intelligent AI agents that can reason, plan, act, and integrate with enterprise systems to automate business processes and enhance user productivity.

• *Key Responsibilities**
• -----------------------

Design and develop enterprise\-grade GenAI and Agentic AI applications.

Build autonomous and semi\-autonomous AI agents capable of reasoning, planning, and executing complex workflows.

Develop Retrieval\-Augmented Generation (RAG) solutions using enterprise knowledge sources.

Integrate LLMs with internal systems, APIs, databases, and business applications.

Create multi\-agent orchestration frameworks for complex business use cases.

Develop copilots, virtual assistants, and AI\-powered decision\-support systems.

Fine\-tune prompts and optimize model performance, latency, and cost.

Build secure, scalable, and production\-ready AI services and APIs.

Collaborate with product managers, architects, and domain experts to define AI solution roadmaps.

Evaluate emerging GenAI technologies and recommend their adoption.

• *Skill Requirements**
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GenAI \& LLMs

Agentic AI

LangGraph

LangChain

CrewAI

Multi\-Agent Systems

Agent Orchestration Frameworks

Tool Calling \& Function Calling

RAG \& Knowledge Systems

Retrieval\-Augmented Generation (RAG)

Vector Databases

Embedding Models

Knowledge Graphs

Python (Mandatory)

FastAPI / Flask

• *Must Have Skill**
• ------------------

LangGraph,Python,Retrieval\-Augmented Generation (RAG),LLM API Integration,CrewAI,Prompt Engineering

• *Good to Have Skill**
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• *Other Requirements**
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Prompt Engineering and Prompt Optimization.

Fine\-tuning and model customization.

Model evaluation and benchmarking.

AI guardrails and responsible AI practices.

REST APIs