• Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets. • Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle. • Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding. • Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows. • Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

• Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets. • Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle. • Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding. • Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows. • Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

• Lead the full delivery of AI and machine learning projects, ensuring timelines, budgets, and quality standards are achieved. • Run and mentor delivery teams, providing clear direction, support, and professional development opportunities. • Develop and maintain comprehensive project plans, risk registers, and delivery roadmaps using appropriate methodologies. • Engage with senior collaborators and clients to understand requirements, lead expectations, and communicate progress and outcomes. • Analyse project performance metrics and implement continuous improvement initiatives to improve delivery efficiency. • Coordinate prioritisation, capacity planning, and team composition to optimise project outcomes. • Identify and mitigate risks proactively, developing contingency plans and protocols for blocking issues. • Champion guidelines in AI delivery, governance, and ethical implementation across the organisation. • Collaborate with technical teams to ensure architectural decisions align with business objectives and delivery constraints. • Facilitate knowledge sharing and capability building within the delivery function.

• Build and productionize multi-agent workflows on Anthropic/OpenAI APIs: orchestration, tool use, structured outputs, guardrails. • Design hybrid retrieval architectures that combine knowledge graphs, vector search, and ranking into a single coherent context layer. • Build evaluation harnesses and observability for agent behavior — quality, latency, cost — and use them to drive iteration. • Integrate LLM inference, retrieval, and reasoning services into production backends. • Work with researchers and domain experts to turn neuro-symbolic prototypes into robust product features.