Staff AI Solutions Engineer

Responsibilities

• Drive integration of the governed agent layer into the data engineering software development lifecycle.
• Build agentic engineering capabilities including skills, specifications, context scaffolding, shared memory, progressive disclosure, and governed data access.
• Define continual learning, post-run review, and agent self-improvement processes that produce reviewable pull requests.
• Advance the strategy-optimization engine into a product capability tied to business metrics.
• Define optimization action spaces, objectives, utility weights, guardrails, risk tolerances, deterministic scorers, experiment definitions, and holdout practices.
• Expand optimization into promotional spend, module placement and ranking, and search relevance.
• Mature the offline simulation environment using synthetic personas based on real behavioral data.
• Establish agreement between simulated and live outcomes and drive simulation adoption in experiment prioritization.
• Act as technical lead by decomposing strategy into specifications, skills, and tickets owned by individual engineers.
• Define the working model between humans and AI agents and raise engineering quality through code, design, and reusable-pattern reviews.
• Mentor engineers across US and Romania pods and represent the team with partner organizations, vendors, and external delivery partners.

Requirements

• 8+ years of software, machine learning, or AI engineering experience, including technical leadership of a system built by other engineers.
• Experience translating ambiguous business problems into measurable objectives, metrics, and guardrails with product partners.
• Breadth to contribute to technical design reviews, product prioritization, and senior-stakeholder discussions.
• Experience decomposing strategic direction into autonomous engineering workstreams.
• Expert-level production Python, including typing, testing, packaging, and performance awareness.
• Hands-on experience using agentic coding harnesses and designing agent skills, context, tool access, and memory.
• Production LLM application experience with agent orchestration, tool and function calling, structured output handling, and retrieval.
• Strong optimization and experimentation experience, including strategy-space search, deterministic scoring, offline/online metric alignment, holdout discipline, and A/B design and interpretation.
• Cloud-native engineering experience on AWS and hands-on experience with a modern data platform such as Databricks.
• Bachelor’s degree in Computer Science or a related technical field, or equivalent industry experience.
• Knowledge of sports or experience in a heavily regulated industry is a plus.

Benefits

• Health plans, including options as low as $0 per paycheck, with fertility and family-planning, mental-health, and fitness programs.
• Paid time off, sick leave, and 14 paid company holidays.
• Annual bonus and long-term incentive opportunities based on performance.
• 401(k) with up to a 5% match.
• Commuter benefits, pet insurance, and other FanDuel Total Rewards benefits.
• Medical, vision, dental, life, and disability insurance may be available.
• The role is listed as hybrid.