Python Developer - GenAI / AI Agent Engineer

Bright Sol

New York, NY, United States

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Cloud Engineering Databases Python (Programming Language) Azure Machine Learning Enterprise Software Applications Large Language Models Multi-Agent Systems Prompt Engineering Generative AI Event Driven Architecture

+5 more

Virtual Agents Restful APIs Automation Anywhere Api Management Microservices

Job description

Design, develop, and deploy scalable applications using Python, REST APIs, microservices, and event-driven architectures.

Integrate AI agents with enterprise applications, databases, APIs, and third-party services.

Build autonomous and multi-agent solutions using Google ADK or Agent SDK.

Implement tool calling, agent orchestration, workflow management, and context management.

Integrate Gemini and/or OpenAI models into enterprise applications.

Develop effective prompts and implement function calling, structured outputs, grounding, and reasoning patterns.

Design and implement Retrieval-Augmented Generation (RAG) solutions using embeddings and vector databases.

Develop and deploy production-ready GenAI applications with appropriate observability, evaluation, security, governance, and guardrails.

Collaborate with engineering and product teams to design scalable and reliable AI-powered solutions.

Requirements

We are looking for a strong Python Developer / GenAI Engineer with hands-on experience building production-grade AI agents, LLM applications, and API integrations. The ideal candidate will have strong Python engineering fundamentals combined with experience in AI agent development, RAG, LLM integration, and production AI engineering., Strong hands-on Python development experience.

Strong experience with REST APIs, microservices, and event-driven architectures.

Hands-on experience with Google ADK or Agent SDK.

Experience developing autonomous and multi-agent AI solutions.

Strong understanding of LLMs, Gemini and/or OpenAI.

Experience with prompt engineering, function calling, structured outputs, grounding, and agent evaluation.

Hands-on experience implementing RAG architectures.

Experience with vector databases and embeddings.

Knowledge of AI observability, evaluation frameworks, security, governance, and guardrails.

Experience deploying and supporting production-grade GenAI applications.

Preferred Experience integrating AI agents with enterprise systems and third-party services.

Experience with multi-agent orchestration and complex AI workflows.

Experience with cloud-based AI/ML platforms.