Agentic AI Developer (or AI Agent Engineer)

Role Descriptions

An Agentic AI Developer (or AI Agent Engineer) focuses on building autonomous AI systems that operate with limited human supervision to achieve complex| goal-driven tasks. Unlike traditional AI engineers who focus on model accuracy (predictive AI)| agentic AI developers create systems that can plan| reason| use external tools| and take actions.

Job Description Agentic AI Developer

Role Summary-

We are seeking an Agentic AI Developer to design and build production-grade| autonomous AI agents capable of reasoning| planning| and executing multi-step workflows. You will integrate Large Language Models (LLMs) with external tools| databases| and enterprise software (APIs) to drive real-world business outcomes across supply chain| customer service| or other enterprise environments.

Key Responsibilities-

• Agentic System Design Architect| build| and optimize AI agents using multi-agent frameworks (e.g.| LangGraph| AutoGen| CrewAI).
• Reasoning Planning Implement advanced prompting strategies| such as chain-of-thought| reflection| and self-correction loops to enhance agent decision-making.
• Tool Integration Connect AI agents to APIs| databases| and third-party SaaS platforms to enable autonomous action-taking.
• Memory Context Design short-term and long-term memory systems (RAG| vector databases) so agents can maintain state and context over long-running workflows.
• Production Deployment Transition prototypes from research to production-ready systems| ensuring low latency| high accuracy| and observability (e.g.| using Amazon Cloud Watch Lang Smith).
• Safety Governance Implement AI guardrails| human-in-the-loop approval steps| and audit trails to ensure ethical and secure operation.

Requirements-

• Strong Python proficiency is essential, along with experience in backend services such as Fast API Flask.
• AI Frameworks: Hands-on experience is needed with Lang Chain, Lang Graph, Auto Gen, or CrewAI.
• LLM Expertise: A deep understanding of prompting techniques, function calling, and context window management using models like GPT-4, Claude, or Gemini is required.
• Data Knowledge: Proficiency in vector databases (e.g., Pinecone, Chroma) and RAG pipelines is necessary.
• Software Engineering: API integration, Docker, Kubernetes, and CICD pipelines are essential.

The Agentic AI Developer will design, build, and operationalize governed AI agent systems that autonomously plan, reason, and execute complex workflows across enterprise data and risk platforms. This role focuses on developing multi agent, event driven AI solutions using Python, LangChain, Lang Graph, and Azure AI Foundry, with strong emphasis on explainability, human in the loop control, and regulatory readiness.