Senior AI Platform Engineer

STRATEGIC STAFFING SOLUTIONS (S3) HAS AN OPENING!

Senior AI Platform Engineer
St. Louis, MO (Only local candidates will be considered)
Hybrid/onsite 3 days a week
12+ Months with opportunity to extend
W2 Contract role

Position Summary
Lead the design and development of an enterprise AI platform that enables agentic workflows across structured and unstructured data. This hands-on role combines software development, platform architecture, AI strategy, and technical leadership to build scalable AI solutions and guide key technology decisions.

You will help evolve our platform from Retrieval-Augmented Generation (RAG) applications to agentic AI systems that leverage reasoning, orchestration, tool use, and autonomous workflows.
Duties:

• Design, build, deploy, and support production AI solutions.
• Develop agentic workflows, tool integrations, and orchestration pipelines.
• Build and evolve RAG and agent-based architectures.
• Create evaluation frameworks to improve quality, groundedness, and reliability.
• Implement AI observability, tracing, and monitoring capabilities.
• Develop automated testing and regression validation processes.
• Integrate AI solutions with APIs, enterprise applications, and data sources. Design reusable AI patterns, frameworks, and components that increase platform scalability and team productivity.
• Establish engineering best practices and contribute to code reviews.
• Research and adopt emerging AI technologies where they provide business value.
• Partner with stakeholders to translate business problems into AI solutions

Required Skills

• 5+ years of software engineering experience.
• Proven track record of delivering enterprise-grade production software.
• Strong Python development skills.
• Experience building, deploying, and operating production AI systems.
• Experience designing and implementing RAG solutions.
• Experience with Databricks.
• Hands-on experience with LangGraph or similar agent orchestration frameworks.
• Experience building AI workflows that leverage tools, APIs, and external systems.
• Experience with AI evaluation frameworks and quality measurement.
• Experience implementing AI observability and tracing solutions.
• Understanding of agent architecture patterns, prompt engineering, and LLM evaluation techniques.
• Experience with AWS in production environments.
• Experience designing and consuming REST APIs.
• Experience with Git, CI/CD, and modern software engineering practices.

*Beware of scams. S3 never asks for money during its onboarding process