Product Owner / Project Design Authority responsible for shaping product direction, managing priorities, and ensuring delivery of digital training and simulation solutions for Thales.
Responsibilities
Act as primary representative of customer and user needs
Manage and prioritise product backlog
Define product requirements, acceptance criteria and functional expectations
Work closely with customers, users and stakeholders to understand priorities
Ensure product development aligns with business and product strategies
Lead a development team responsible for maintaining the continuous flow of new software enhancements and deployments for NDOC mission applications.
Compensation
Pay Range $131,300.00 - $237,350.00
Responsibilities
Provide technical leadership for design, development, integration, deployment, and sustainment of NDOC mission applications
Collaborate with government stakeholders and engineering teams to translate mission requirements and roadmap priorities into actionable development plans
Engineering point of contact for delivering complex AI applications at YouTube, transitioning prototypes to production-grade solutions.
Responsibilities
Serve as the engineering point of contact for delivering complex AI applications, transitioning from rapid prototypes to production‑grade, AI‑powered solutions (e.g., multi‑agent systems, MCP servers) that drive measurable return on investment.
Execute the full software development lifecycle, authoring technical design documents and project plans, writing, testing, and shipping clean, maintainable code, building intuitive frontend surfaces, and executing delivery from initial scoping through to deployment.
Prototype rapid proof‑of‑concepts (PoCs) using frontier GenAI (e.g., LLMs, RAG, agentic frameworks) to demonstrate technical feasibility to stakeholders, translating ambiguous business problems into tangible software solutions.
Build high‑performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, compliance and latency.
Identify and systematically resolve the technical issues that prevent AI from reaching maturity, including data readiness gaps, system integration complexities, edge‑case management, and state‑management challenges.
Requirements
Bachelor's degree in Computer Science, Electrical Engineering, Math or a related quantitative field, or equivalent practical experience in software development
