Lead AI Platform Engineer

ZipStaff•St. Louis, MO

6h•Onsite

About The Position

ZipStaff is seeking a Lead AI Platform Engineer to design, build, and operate production AI solutions for a major energy and utilities organization. This is a hands-on technical leadership role focused on agentic workflows, RAG architectures, evaluation frameworks, and AI observability. You will establish reusable AI patterns, raise engineering standards, and deliver enterprise-grade AI systems that are reliable, measurable, and integrated with existing APIs, applications, and data sources.

Requirements

7–8+ years of software engineering experience with a 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.
Hands-on 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
Knowledge of secure coding principles and responsible AI practices.
Experience collaborating within Agile software development teams.
Ability to work on-site in St. Louis, MO.
Must be legally authorized to work in the United States without sponsorship now or in the future.

Nice To Haves

Experience with AgentBricks.
Experience with Microsoft Copilot extensibility and agent development.
Experience with LangChain and related frameworks.
Experience with MCP integrations.
Experience with vector databases and semantic search.
Experience with AWS Bedrock.
Experience with OpenTelemetry, LangSmith, Grafana, MLflow, DeepEval, or similar tooling.
Experience deploying multi-agent systems.
Experience with Terraform.
AWS, Databricks, Microsoft, or AI-related certifications.

Responsibilities

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.