• Architect and implement a robust agentic framework that supports tool use, context retrieval, memory, and planning • Build intelligent, modular agents that automate investigative tasks and augment analyst decision-making • Extend and scale our LLM infrastructure (e.g. OpenAI, Anthropic, local models), including prompt engineering, RAG, and evaluation loops • Design safe, observable, and auditable agent behaviors — ensuring reliability in high-sensitivity environments • Evaluate performance across metrics like reasoning, latency, success rate, and hallucination, and iterate based on user feedback and system telemetry • Contribute to a culture of high ownership, rapid experimentation, and ethical AI deployment

• Work on complex engineering problems that help you build and hone not only technical skills but also project management and human/soft skills. • Develop and maintain public APIs that are part of the API Product suite • Collaborate with stakeholders on transforming a functional vision into a tangible roadmap with clear outcomes. • Support and enable internal business units through shared engineering services and functionalities. • Develop cross-functional relationships with stakeholders across the organization to understand and empower their mission from end to end.

• Writes and maintains code within applications and systems to implement capabilities and features • Improves performance and maintainability, while reducing technical debt in alignment with product and technology roadmaps • Plays a role in Agile planning, providing advice and guidance, and monitoring emerging trends • Works with Product Management to understand the challenges that customers and end users face in their day-to-day work • Recommends viable solutions to processes, technology, and interfaces that improve the effectiveness of the team • Contributes to product and solution designs to address critical issues and complex problems • Builds software applications across multiple platforms in response to the needs of stakeholders • Provides ongoing support, monitoring, and maintenance of deployed products • Actively participates in the engineering community, staying up to date on new software technologies and best practices

• Own the workstreams and components you are responsible for, from design through production, inside the client's environment. • Participate in discovery, architecture reviews, and stakeholder interviews on your area of the engagement; turn vague problems into scoped, deliverable work. • Make the build and design decisions appropriate to the client's environment and constraints on the work you own, and stand behind them. • Build the system: production data pipelines, LLM applications, agents, and workflow automations that meet spec and hold up under real load. • Manage scope actively on your workstreams: surface risk and creep before it becomes a problem, not after. • Transfer capability that lasts: documented, runnable, maintainable software that works after you leave. • Build trusted relationships with client stakeholders while supporting the Architect or AI Lead in overall account ownership. • Contribute reusable patterns and lessons learned that improve future delivery.