Agentic AI Engineer

KEY RESPONSIBILITIES

Agentic Architecture & Implementation: Design, build, and maintain autonomous AI agents using

frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel.

Multi-Agent Collaboration: Develop collaborative multi-agent orchestration systems that support task

planning, dynamic reasoning, tool-use execution, self-correction, and structured feedback loops.

System & Tool Integration: Create custom tools, APIs, and retrieval mechanisms (RAG) that connect LLM

agents to internal enterprise platforms (SAP, POS systems, inventory databases, supply chain APIs).

Model Fine-Tuning & Prompting: Improve prompts, apply advanced prompt engineering techniques,

and fine-tune open/closed-source LLMs (OpenAI, Claude, Llama) for agent-specific execution tasks.

Production Deployment & Evaluation: Roll out agentic pipelines in cloud environments (Azure/AWS) with

full observability, latency optimization, cost management, and dependable fallbacks.

Cross-Functional Partnership: Work with data engineers, product managers, and business

stakeholders to convert retail operational challenges into scalable autonomous agent workflows.

TECHNICAL REQUIREMENTS & QUALIFICATIONS

Experience: Minimum of 3+ years of software engineering experience, including at least 1+ years focused on

building LLM applications, RAG pipelines, or Agentic AI systems.

Programming Mastery: Advanced proficiency in Python (FastAPI, Asyncio, Pydantic) with clean, modular,

and maintainable code architecture.

Agentic Frameworks: Practical experience with modern agent frameworks such as LangGraph, AutoGen,

CrewAI, LlamaIndex, or OpenAI Assistants API.

Tool Use & Reasoning: Proven experience implementing Function Calling, ReAct patterns, Tree-of-

Thoughts, and stateful agent memory architectures (short-term & long-term).

Vector Databases & RAG: Hands-on experience with vector stores (Pinecone, Qdrant, Chroma, Weaviate, or

Pgvector) for contextual grounding and knowledge retrieval.

Cloud & DevOps: Strong understanding of cloud infrastructure (Azure / AWS / GCP), containerization (Docker,

Kubernetes), and CI/CD development standards.

Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a

related technical discipline.

PREFERRED & NICE-TO-HAVE SKILLS

Prior experience with retail, e-commerce, customer service automation, or supply chain technology.

Familiarity with agent evaluation framework tools (e.g., Ragas, TruLens, LangSmith, Arize Phoenix).

Experience using local LLM serving tools (vLLM, Ollama) and model quantizations.

Knowledge of fine-tuning methods (LoRA, QLoRA) for specialized task execution