GenAI​/LLM engineering

Role: GEN AI Engineer

Role Overview
The candidate will be responsible for designing, building, and deploying agentic AI solutions using modern frameworks and LLM technologies. The role will focus on multi-agent orchestration, AI reasoning, tool integration, knowledge retrieval, and production-scale AI platforms.

Key Responsibilities

Develop autonomous AI agents capable of planning, reasoning, and task execution.
Build and orchestrate multi-agent workflows using Lang Graph or similar frameworks.
Integrate LLMs such as Claude/GPT through AWS Bedrock and other enterprise AI services.
Develop MCP-based tools and integrations for APIs, document processing, search, analytics, and reporting.
Build scalable Python services, APIs, ETL pipelines, and data integrations.
Implement RAG, vector search, and knowledge retrieval solutions.
Ensure observability, monitoring, auditability, security, and AI governance controls.
Develop Human-in-the-Loop (HITL) workflows and validation mechanisms.

Mandatory Skills

Python, FastAPI, REST APIs
Lang Graph and Agentic AI frameworks (Claude Agent SDK, CrewAI, Auto Gen, Semantic Kernel, etc.)
Multi-Agent Systems and Workflow Orchestration
Claude/GPT Models and AWS Bedrock
Prompt Engineering and Context Engineering
PostgreSQL, pg Vector, Vector Databases, RAG
AWS, Docker, ECS/EKS, CI/CD
AI Governance, Monitoring, and Audit Controls

Preferred Skills

MCP Server Development
Knowledge Graphs
Multi-modal Document Processing
Agent Evaluation & Monitoring Frameworks
Sustainability / Climate Data Platforms
AWS Solution Architecture Certification

Experience

3+ years of GenAI/LLM engineering experience.
Proven experience building production-grade AI agents and cloud-native platforms.
Strong understanding of AI governance, risk controls, and enterprise deployment practices.