Lead AI Engineer

We are building a unified GenAI Platform that helps hundreds of product teams create, test, and deploy AI agents quickly and safely. As a Lead AI Engineer, you will deliver end-to-end agents and platform modules, improve CI/CD and observability, and guide architecture and execution across major initiatives. Join us and apply today

Responsibilities

• Deliver end-to-end applications, AI agents, and platform modules that enable rapid GenAI agent creation, evaluation, and deployment
• Develop developer tooling, automate CI/CD workflows, and strengthen observability for secure delivery cycles, including evaluation frameworks, canary releases, rollbacks, and monitoring of cost and quality
• Embed secure development lifecycle and privacy-first practices, including threat analysis and least-privilege enforcement
• Collaborate with product owners, UX specialists, and subject matter experts to build user-focused solutions with measurable impact
• Apply modern LLM techniques such as retrieval-augmented generation, intelligent routing, tool integration, and evaluation to improve reliability, reduce decision time, increase trust and safety, and optimize query costs
• Provide technical leadership by defining architecture, mentoring engineers, and driving large initiatives

Requirements

• Hands-on software engineering experience of 5+ years in production environments
• At least 1 year of experience leading and supervising engineering teams
• Proven track record of shipping software independently or with small, fast-moving teams
• Practical experience taking AI agents from idea to production, including safety checks, A/B testing experiments, and iterative improvements
• Proficiency with LangChain or LangGraph, MCP, vector databases, and OpenSearch
• Solid understanding of machine learning workflows, including model training, deployment, and monitoring
• Knowledge of compliance frameworks such as SOC2 and HIPAA
• Strong analytical thinking, clear communication, and an ownership mindset
• Advanced full-stack development skills with familiarity in cloud environments such as AWS, Azure, or GCP
• Experience with CI/CD automation and Infrastructure as Code practices
• Understanding of Site Reliability Engineering concepts and operational reliability
• Background in quality assurance practices and testing methodologies
• Awareness of secure development lifecycle and privacy-first engineering approaches
• Strong TypeScript skills in real-world applications
• English proficiency at B2+ (Upper-Intermediate) or higher, written and spoken

Nice to have

• Understanding of how large language models work, their limitations, and approaches such as fine-tuning and model customization
• Experience building Retrieval-Augmented Generation (RAG) applications