Lead AI Platform Engineer

Lead AI Platform Engineer

Job Id: AEE1JP00002803

Location: St. Louis, MO - 3 days/week onsite

Duration: 6-month contract-to-perm

Visa Eligibility: USC, GC, GC EAD

Interview Process: 1st round video interview; 2nd round in-person

LinkedIn with location (before 2022)

Critical Requirements

Candidates should have strong evidence of all three of the following:

1. Production agentic AI experience - not merely a proof of concept or pilot.
2. LangGraph or comparable agent orchestration experience in a production environment.
3. 5+ years of software engineering experience with enterprise-grade deliverables.

Internal Hiring Manager Notes - Do Not Share with Candidates

• Three primary must-haves: production agentic systems, implementation/monitoring/evaluation of those systems, and 5+ years of software engineering.
• Production agentic AI with LangGraph is required; pilot-only experience is insufficient.
• Enterprise platform experience should be platform-agnostic.
• Databricks, MCP, AWS Bedrock, Agent Bricks, Datadog, and CloudWatch are differentiators.
• The role does not require prior people-management or team-lead experience.
• The engineer will work alongside the manager, who will provide overall direction.
• Candidate should be comfortable discussing token cost, latency, observability, throttling, and performance optimization.

Position Overview

Client is seeking a Lead AI Platform Engineer to design, build, deploy, and support enterprise-grade AI solutions and platforms. This is a hands-on engineering role focused on building scalable agentic AI systems , RAG architectures, AI workflows, and platform capabilities across structured and unstructured data.

The ideal candidate will have strong software engineering fundamentals, proven experience delivering production agentic AI systems , and hands-on experience with LangGraph or similar agent orchestration frameworks . The role will work closely with engineering leadership, stakeholders, and technical teams to build and evolve an enterprise AI platform.

Required

• 5+ years of professional software engineering experience.
• Proven experience delivering enterprise-grade production software .
• Strong hands-on Python development experience.
• Experience building, deploying, and operating production AI systems .
• Proven experience designing and implementing production agentic AI systems .
• Hands-on experience with LangGraph or a comparable agent orchestration framework .
• Experience building AI workflows that leverage tools, APIs, and external systems.
• Strong experience designing and implementing RAG solutions .
• Experience with Databricks .
• Experience with AI evaluation frameworks and quality measurement.
• Experience implementing AI observability, tracing, and monitoring solutions.
• Understanding of agent architecture patterns, prompt engineering, and LLM evaluation techniques.
• Production experience with AWS .
• 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 working within Agile software development environments.

Qualifications

• Experience with Databricks Agent Bricks in a meaningful production or enterprise capacity.
• Experience with MCP integrations .
• Experience with AWS Bedrock .
• Experience with observability tools such as Datadog and Amazon CloudWatch .
• Experience optimizing AI application performance, including latency, throughput, throttling, and cost.
• Experience balancing model performance, response speed, token consumption, and infrastructure constraints.
• Strong communication skills and a willingness to collaborate, mentor, and support teammates.
• Self-motivated and comfortable working closely with engineering leadership and business stakeholders.