- Salary
- $40 – $50
- Location
- Farmington Hills, Michigan, United States
- Workplace
- Hybrid
- Type
- Contract
- Department
- Information Technology
- Seniority
- Senior
- Experience
- 8+ years
- Source
- Recruitee
Description
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.