About this role
Position Summary
The AI Software Engineer III will be responsible for designing, developing, and supporting secure, scalable AI-enabled applications. The role focuses on Python development, Generative AI, prompt engineering, Retrieval-Augmented Generation (RAG), document intelligence, AI agents, and enterprise AI integration.
- Location: Farmington Hills, MI (Onsite – 4 days per week) Experience: 8+ Years Work Arrangement: Onsite – Local candidates strongly preferred Key Responsibilities Design and develop production-quality applications and AI services using Python.
- Build Generative AI capabilities using Amazon Bedrock and Large Language Models (LLMs).
- Design, develop, test, and optimize prompts, including prompt templates, structured outputs, and reusable prompt patterns.
- Develop RAG, intelligent search, embedding, and vector retrieval solutions.
- Build AI agents and agent-based workflows using frameworks such as Strands Agents.
- Develop reusable AI services and APIs using FastAPI and Pydantic.
- Integrate AI solutions with structured and unstructured enterprise data.
- Support document processing and extraction using Amazon Textract.
- Implement vector-based retrieval using PostgreSQL/pgvector.
- Establish safeguards for AI output quality, reliability, validation, traceability, and secure data handling.
- Optimize AI solutions for performance, latency, token usage, and cost.
- Develop automated testing and evaluation capabilities for AI solutions.
- Collaborate with application, data, DevOps, QA, architecture, cybersecurity, and business teams.
Required Qualifications
- 8+ years of experience in Python development, software engineering, AI/ML engineering, or related fields.
- Strong hands-on experience with Python, REST APIs, FastAPI, Pydantic, and boto3.
- Experience with Amazon Bedrock, LLM integration, and Generative AI solutions.
- Strong expertise in prompt engineering, including prompt design, testing, optimization, structured outputs, and evaluation.
- Experience with RAG, embeddings, semantic search, vector databases, and PostgreSQL/pgvector.
- Experience developing AI agents and agentic workflows, preferably using Strands Agents.
- Hands-on experience with Amazon Textract, AWS, Docker, and automated testing.
- Strong understanding of AI security, data protection, responsible AI, and enterprise governance.
- Experience working in large enterprise or regulated environments.
- Interview Process Internal Technical Screening: 20–30 minutes.
- Client Interview: Virtual.