GenAI Engineer (Agent Development)

Generative AI Engineer - Agent Development Specialist

Our Big 4 client is seeking an experienced Generative AI Engineer Consultant with expertise in agent-based system development to support a major client. In this role, you will design, implement, and optimize intelligent multi-agent workflows that power next-generation applications. The ideal candidate is highly skilled in Python, AI agents, vector databases, and multi-agent orchestration frameworks, and is motivated to bring autonomous AI agents into production environments.
Key Responsibilities

• Design, build, and maintain autonomous and semi-autonomous AI agents using frameworks such as LangGraph (preferred), Autogen, CrewAI, or Bedrock.
• Develop sophisticated prompting strategies to ensure consistent, reliable, and effective agent performance across dynamic use cases.
• Architect end-to-end agent solutions integrating vector databases (e.g., Azure AI Search, FAISS, Pinecone, Chroma) with real-time and batch ETL pipelines for retrieval-augmented generation (RAG).
• Leverage CosmosDB and other NoSQL data stores to manage unstructured and semi-structured datasets at scale.
• Collaborate with product, engineering, and data teams to integrate AI agents into APIs, applications, and enterprise workflows.
• Stay up to date with the latest GenAI models, frameworks, and design patterns, and evaluate their applicability to production use cases.
• Conduct performance tuning, observability, and safety evaluations of AI agents across varied environments.
• Participate in code reviews and maintain engineering best practices using Git/GitHub workflows (branching, PRs, CI/CD).

Required Qualifications

• Strong programming skills in Python with a solid grasp of OOP principles and production-level code.
• Hands-on experience with prompt engineering techniques for LLMs (GPT, Claude, Gemini, or open-source equivalents).
• Deep understanding of AI agent concepts: memory management, planning, tool use, autonomous task execution, and evaluation metrics.
• Experience with multi-agent orchestration frameworks, ideally LangGraph, but Autogen, CrewAI, or similar are also valuable.
• Proficiency with vector databases (Azure AI Search, Pinecone, FAISS, Chroma) for embeddings and semantic search.
• Understanding of ETL processes and data pipelines (batch and streaming).
• Familiarity with NoSQL databases (CosmosDB preferred) and scalable schema design.
• Experience with Git/GitHub workflows, including Gitflow or similar collaborative practices.
• Strong awareness of current GenAI trends, models, and protocols (e.g., OpenAI Assistants, function calling, LangChain Agents).

Preferred Qualifications

• Experience deploying AI agents in cloud environments (Azure, AWS, or Google Cloud Platform).
• Familiarity with fine-tuning models, embeddings generation, and plugin/tool calling in LLM ecosystems.
• Exposure to AI evaluation methods, such as human-in-the-loop and automated feedback loops.
• Contributions to open-source AI projects or publications in the field.
• Bonus: Exposure to AngularJS and TypeScript for specific use cases.

Core Skills

• Python
• Prompt Engineering
• Multi-Agent Orchestration (LangGraph, Autogen, CrewAI, etc.)
• Vector Databases (Azure AI Search, Pinecone, FAISS, Chroma)
• NoSQL / CosmosDB
• ETL & Data Pipelines
• Agile / Scrum (CSP, CSPO)
• RESTful APIs
• Conversational Agents & Application Architecture

#LI-SB1
#Dice