Mentor, inspire, and grow a diverse team of engineers, fostering a culture of craftsmanship, curiosity, and continuous learning in applied AI.
Manage the team through hiring, retaining, mentoring, and continuously building individual and team capabilities in modern AI engineering best practices.
Act as an embedded engineering partner to the product organization, championing AI-first approaches to feature delivery and accelerating squads' ability to leverage AI infrastructure.
Lead the technical direction and execution for AI initiatives, including agent workflow development, MCP tooling, and the internal AI chat assistant.
Develop and nurture strong relationships with Product, QA, Delivery, Design, Customer Support, GTM, and other partners to deliver best-in-class AI-powered experiences.
Own end-to-end build and delivery of AI solutions, features, and services within Optro's platform, collaborating closely with the AI Platform team for core infrastructure.
Continuously improve all aspects of the product lifecycle, technical systems, engineering processes, and team practices, to deliver outstanding results for customers.
Collaborate closely with Product Management to define goals, objectives, and the roadmap for AI Applications initiatives, ensuring alignment with business priorities.
Champion agile best practices, ensuring clarity, transparency, and efficient delivery across your team and the broader organization.
Requirements
5+ years of engineering experience, with 2+ years in an engineering management role leading teams building and shipping production AI or software systems.
Demonstrated ability to be a technical mentor and engineering role model, someone engineers look to for guidance on architecture, code quality, and engineering culture.
Strong proficiency with Python and modern server-side development; comfort with TypeScript/Node.js is a plus.
Experience with AWS (preferred) or Azure cloud environments and modern deployment practices.
Track record of partnering with Product teams to drive delivery velocity and quality.
Solid understanding of modern agent frameworks and how to apply them to build reliable, production-grade AI workflows (e.g., LangGraph, LangChain, or comparable tooling).
Experience deploying agents in production including observability, tracing, failure handling, and performance considerations.
Familiarity with vector databases, semantic search, or RAG-adjacent technologies at the application integration level.
Familiarity with the Model Context Protocol (MCP) and experience building or consuming tool-based AI integrations.
Bonus: Experience building or maintaining AI-assisted chat or conversational interfaces.
Bonus: Experience with modern JavaScript frameworks (Ember preferred; Vue, React, or Angular also valued) for front-end collaboration.
Bonus: Understanding of ethical AI principles and responsible AI development practices.
Bonus: Experienced working in a highly regulated, ARC (Audit, Risk, and Compliance) environment.
Preferred: Managed remote or distributed engineering teams.
Preferred: Experience in an agile development environment and with modern project management tooling.
Preferred: Strong B2B SaaS product experience.
Preferred: Comfort operating in a fast-moving environment where the AI tooling landscape evolves rapidly.