Lead AI Engineer – Production AI & Agentic Systems

Strategic Staffing Solutions; United States; Hybrid; USD 165,000 - 276,000; Full time

Job summary

Strategic Staffing Solutions seeks a Lead AI Engineer to design, build, and operate enterprise AI solutions in a hybrid St. Louis, MO environment. You will advance the platform from RAG apps to agentic AI systems with reasoning, orchestration, and tool use.

You will partner with platform engineers and stakeholders to ensure production systems are evaluable, observable, and reliable, delivering measurable business value.

Qualifications

• 5+ years of software engineering experience.
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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 apps, and data sources.
• Design reusable AI patterns, frameworks, and components for scalability.
• Establish engineering best practices and participate in code reviews.
• Research and adopt emerging AI technologies with business value.
• Collaborate with stakeholders to translate business problems into AI solutions.

Skills

Python

Production AI

RAG

Agent orchestration

AWS in production

REST APIs

Git & CI/CD

Agile teams

Observability & tracing

Databricks

LangGraph or similar

Security & best practices

Tools

Databricks

LangGraph

AWS

OpenTelemetry/Grafana/MLflow tooling

Job description

Strategic Staffing Solutions seeks a Lead AI Engineer to design, build, and operate enterprise AI solutions in a hybrid St. Louis, MO environment. You will advance the platform from RAG apps to agentic AI systems with reasoning, orchestration, and tool use.

You will partner with platform engineers and stakeholders to ensure production systems are evaluable, observable, and reliable, delivering measurable business value.