Description

Job Description:
We are seeking a strong AI Software Developer with 3–5 years of recent, hands-on Python development experience.
This is not simply a Python Developer position. The ideal candidate will be a well-rounded Software Developer with a strong background designing, developing, testing, and deploying production-quality applications, along with recent hands-on Python experience.
The position will focus on developing and implementing Generative AI and Agentic AI solutions, including LLM-powered applications, RAG solutions, prompt engineering, NLP, and AI agents/workflows.
The engineer will collaborate with product managers, architects, data engineers, data scientists, ML engineers, and business stakeholders to integrate AI capabilities into applications, products, workflows, and business processes.

Additional Notes:
• 3–5 years of recent Python development is a key requirement.
• The manager wants a well-rounded Software Developer, not someone focused solely on Python scripting.
• Strong hands-on GenAI / LLM experience is important.
• Agentic AI experience is highly desirable.
• Candidates should have experience building production-quality software solutions.
• Candidate experience should justify the submitted rate.
• The top rate should be reserved for exceptional candidates who closely match the complete technical requirements.
• There are currently 2 openings.
• Candidates must be able to convert to permanent employment without sponsorship.
• Candidates located in CA, IL, NJ, NY, MA, HI, AK, OR, or WA cannot be considered.
• Automotive insurance claims experience is preferred but not required.

Responsibilities:
• Design, develop, test, and deploy production-quality software and AI applications.
• Develop GenAI and Agentic AI solutions using Python.
• Design, develop, test, and optimize prompts for Large Language Models.
• Build and integrate Retrieval-Augmented Generation (RAG) solutions.
• Develop AI agents and multi-agent workflows using tools such as Azure AI Foundry, CrewAI, or similar frameworks.
• Implement Agentic AI solutions throughout the solution development lifecycle.
• Apply Agentic AI design patterns including Tool Use, Reflection, and Planning.
• Develop effective AI interactions through programming and AI development environments.
• Conduct A/B testing on prompt variants, AI workflows, and automation solutions.
• Analyze model behavior, AI-agent paths, deviations, and performance degradation.
• Collaborate with product managers, data scientists, ML engineers, architects, data engineers, and business stakeholders.
• Integrate GenAI and Agentic AI capabilities into existing products, applications, and business workflows.
• Create reusable AI libraries and technical documentation.
• Support AI observability, monitoring, explainability, and governance initiatives.
• Implement explainability frameworks utilizing technologies such as Model Context Protocol (MCP) and SHAP.
• Follow data-quality, security, governance, compliance, and responsible-AI practices.
• Develop appropriate AI safety controls and filters.
• Stay current with advancements in LLMs, RAG, prompt engineering, NLP, and Agentic AI.
• Provide technical guidance and mentorship to junior team members

Key Skills

Education

Any Graduate