Lead AI Engineer

Role Overview

• Implement Sophisticated AI Agents: Design, build, and deploy complex AI agents using LangChain and LangGraph. You will own the core logic that automates intricate decision-making within the claims lifecycle.
• Master Prompt & Context Engineering: Design, test, and refine complex prompts and contextual data frameworks to ensure our AI agents perform with maximum accuracy, efficiency, and reliability.
• Lead AI Research & Innovation: Stay at the bleeding edge of AI. You’ll be responsible for identifying, prototyping, and integrating the latest foundational models, RAG techniques, and agentic frameworks to solve unique business challenges.
• Build for Production Scale on GCP: Engineer and operate our AI systems in a scalable, reliable production environment on Google Cloud Platform. Your work will directly impact millions of users.
• Champion MLOps for Agentic Systems: Establish and lead best practices for the reliability, versioning, monitoring, and observability of our AI agents, using tools like Langfuse to ensure production-grade performance.
• Collaborate to Deliver Impact: Partner closely with product leaders, data scientists, and other engineers to translate business needs into technical reality, ensuring our AI solutions are both innovative and effective.
• Champion modern software development practices by actively using AI code-assist tools (e.g., Gemini code assists, Github Copilot, Claude code) to accelerate development cycles, generate documentation, improve code quality, testing, and monitoring & observability practices.
• Build, manage, and mentor a cross-functional team of software, quality, and reliability engineers, fostering a culture of technical excellence and continuous improvement.
• Define and report on key engineering metrics (SLA, SLO, SLI) and ensure compliance with security, quality, and financial operations (DevSecOps, FinOps) best practices.
• Collaborate with product managers, architects, SREs and business partners to define technical strategy, create software roadmaps, and make key architectural and design decisions.
• Lead troubleshooting efforts to resolve production and customer issues, demonstrating deep technical expertise and problem-solving skills.
• Participate and lead agile team activities, including Sprint Planning and Retrospectives, to ensure efficient and predictable delivery.
• Lead with a data/metrics driven mindset with a extreme focus towards optimizing and creating efficient solutions.
• Drive up-to-date technical documentation including support, end user documentation and run books.
• Create and deliver technical presentations to internal and external technical and non-technical stakeholders communicating with clarity and precision, and present complex information in a concise format that is audience appropriate.

Requirements

• Bachelor's degree or equivalent experience
• 7+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.
• 2+ years in a dedicated AI/ML role, with hands-on experience in model integration, MLOps, and applying AI to solve business problems.
• 1+ years of direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
• 2+ years of in-depth experience with Google Cloud Platform (GCP), specifically its AI/ML services (Vertex AI, etc.).
• 3+ years of proven experience leveraging Kubernetes workloads.
• Proficiency in Python, JavaScript/TypeScript and/or Java and working knowledge of a modern front-end framework (Angular, React, or Vue) to collaborate effectively with UI teams.
• Hands-on experience with LLM observability tools like Langfuse for monitoring and debugging agentic workflows.

Tech Stack

• Angular
• Cloud
• Google Cloud Platform
• Java
• JavaScript
• Kubernetes
• Python
• React
• TypeScript
• Vue.js

Benefits

• comprehensive compensation and healthcare packages
• 401k matching
• paid time off
• organizational growth potential through our online learning platform with guided career tracks