38173 | Lead AI, Software Engineer

Brilliant Agent•Saint Louis, MO

20d•Hybrid

About The Position

A large enterprise organization is seeking a Lead AI Engineer to help drive a major technology transformation effort. You will guide a team in building cloud-native solutions, scalable APIs, microservices, and AI agents while leveraging modern development practices and AI-powered coding assistants. This role requires strong architectural expertise, cloud depth, and leadership skills. Onsite presence is required three days per week (Tuesday through Thursday).

Requirements

Bachelor's degree or equivalent experience
7+ years of software engineering experience delivering scalable systems
Experience in AI or ML including model integration and MLOps
Hands-on experience with agentic frameworks such as LangChain or LangGraph
Strong experience with a major cloud platform and its AI/ML services
3+ years working with Kubernetes workloads
Proficiency in Python, JavaScript/TypeScript, and/or Java
Familiarity with front-end frameworks such as Angular, React, or Vue
Experience with LLM observability tools (such as Langfuse)
Cloud-native skills including: Docker containerization, Kubernetes orchestration, Infrastructure as Code (Terraform or CloudFormation), CI/CD tools such as GitHub Actions, Argo CD, or Jenkins
Experience with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB, Firestore)

Nice To Haves

Expertise in Generative AI and models such as Gemini, ChatGPT, Claude, or Llama
Experience using AI-powered code assistants to accelerate development
Background deploying AI agents into production environments
Strong ability to solve complex and ambiguous technical challenges
Clear communication skills and experience mentoring engineers
Passion for applying advanced AI to real-world, large-scale problems

Responsibilities

Design, build, and deploy advanced AI agents using frameworks such as LangChain and LangGraph
Develop and refine prompt engineering and context management frameworks
Research and integrate emerging AI models, RAG techniques, and agentic frameworks
Architect and operate production-scale AI systems in cloud environments
Establish MLOps best practices for reliability, monitoring, and observability (including Langfuse)
Collaborate with product, data science, and engineering teams to deliver scalable solutions
Champion modern development practices using AI code-assist tools
Manage and mentor software, quality, and reliability engineers
Define and maintain engineering metrics including SLA, SLO, and SLI
Partner with product managers, architects, and SREs on strategy and roadmaps
Lead production troubleshooting and issue resolution
Participate in agile ceremonies such as Sprint Planning and Retrospectives
Maintain technical documentation, runbooks, and support guides
Deliver clear technical presentations to both technical and non-technical audiences