Staff AI Solutions Engineer

About the role

FanDuel is looking for a Staff AI Solutions Engineer in Atlanta, Georgia, to own the AI technical vision across its portfolio. The role also holds and evolves the technical vision of the governed agent layer, the strategy-optimization engine and the simulation environment, making architectural decisions, writing design documents and decision records, and acting as the trusted technical voice for product teams.

Key responsibilities

• Drive AI into the engineering lifecycle: integrate the agent layer into the data engineering SDLC, from requests coming from Slack, Jira, GitHub and PagerDuty through planning, specification, build, test, PR and documentation.
• Build the environment for agentic engineering: skills, specs, context scaffolding, shared memory and progressive disclosure.
• Extend governed, audited data access so agents operate under each user's own permissions.
• Define the outer loop: continual learning, post-run review and agent self-improvement delivered as reviewable pull requests.
• Turn the strategy-optimization engine into a product capability, partnering with product to turn ambiguous problems into optimizable ones and defining action space, objectives, utility weights, guardrails and risk tolerance.
• Own the deterministic scoring backbone: versioned scorers, shared and immutable experiment definitions and blind holdout discipline, then expand the engine to domains such as generosity, promotional spend, module placement, ranking and search relevance.
• Mature an offline simulation environment so product hypotheses can be pre-screened against synthetic personas, and drive adoption of simulation as a standard input to experiment prioritization.
• Act as the team's technical lead: decompose strategy into specs, skills and tickets, set the working model for an AI-driven team, mentor engineers across US and Romanian pods, and represent the team with partners, vendors and external delivery partners.

Required profile

• 8+ years of software, machine learning or AI engineering experience, including technical leadership of a system other engineers built.
• Track record of turning ambiguous business problems into measurable ones, defining objectives, metrics and guardrails with product partners.
• Credible in technical design reviews, product prioritization conversations and in front of senior stakeholders.
• Bachelor's degree in Computer Science or a related technical field, or equivalent industry experience.
• Knowledge of sports and/or experience in a heavily regulated industry is a plus.

Required skills

• Expert-level Python in production settings, with typing, testing, packaging and performance awareness.
• Hands-on experience with agentic coding harnesses, including skills, context, tool access and memory.
• Production LLM application experience, agent orchestration, tool and function calling, structured output handling and retrieval.
• Strong optimization and experimentation background: search over strategy spaces, deterministic scoring, offline/online metric alignment, holdout discipline and A/B design and interpretation.
• Cloud-native engineering on AWS and hands-on work in a modern data platform such as Databricks.

What we offer

• A range of health plans, some as low as $0 per paycheck, including fertility and family planning, mental health support and fitness benefits.
• Paid time off and sick leave, annual bonus and long-term incentives based on performance.
• 401k with up to a 5% match and commuter benefits.