Lead AI Engineer
Own the technical strategy and hands-on delivery of an enterprise internal AI capability. You will design production agents, shared AI platform services, context and evaluation layers, and secure workflows while advising leadership and partnering with teams across the organization.
Responsabilidades
- Set the technical strategy, target architecture, model and vendor choices, and build-versus-buy decisions for internal AI.
- Shape the AI portfolio by prioritizing workflows, defining success metrics, and challenging low-value initiatives.
- Establish ROI, security, access-control, cost, adoption, cycle-time, and auditability standards for AI systems.
- Advise leadership and review AI initiatives across the organization.
- Develop reusable AI platform patterns, shared services, and engineering standards.
- Mentor AI Champions and manage the internal AI Champions community.
- Evaluate models, vendors, and frameworks.
- Design, build, deploy, and own production AI agents and workflows from prototype through launch.
- Build the AI context layer, including connectors, APIs, retrieval services, metadata, identity, authorization, controls, and tool interfaces.
- Create secure agent action tools and supporting infrastructure.
- Develop RAG, tool-calling, structured-output, and multi-step agentic workflows.
- Define evaluation datasets and automated quality checks for accuracy, groundedness, task completion, safety, and cost.
- Work with business owners to map processes, test with users, and decide whether pilots should scale or stop.
Requisitos
- At least 4 years of production software engineering experience.
- Strong Python, API development, testing, CI/CD, data contracts, and cloud services experience.
- Evidence of senior technical scope, including setting direction, making architecture decisions, and owning systems end to end.
- Ability to translate ambiguous business needs into technical plans and explain trade-offs to non-technical stakeholders.
- A strong ownership mindset focused on measurable business and process outcomes.
Se valora
- Experience as an early AI hire or in establishing an internal AI platform or function.
- Product management experience.
- Experience building internal platforms or company-wide data products.