• Drive the integration of our agent layer into the data engineering SDLC: requests arriving from Slack, Jira, GitHub, and PagerDuty, routed into a planning phase that produces scoped, reviewable tickets and a build phase that carries each ticket through spec, plan, build, test, PR, and documentation.
• Build the environment that makes agentic engineering actually work: skills, specs, context scaffolding, shared memory, and progressive disclosure.
• Extend governed, audited data access so agents operate under each user’s own permissions against our data platform, with a limited blast radius by design.
• Define the outer loop: continual learning, post-run review, and agent self-improvement that lands as reviewable pull requests rather than uncontrolled drift.

Make Optimization a Product Capability

• Advance our strategy-optimization engine from proof of concept to a capability product teams request by name, and land it against real business metrics.
• Partner with product to turn ambiguous business problems into optimizable ones: define the action space, the objective and utility weights that encode the tradeoffs we actually care about, and the guardrails and risk tolerance that keep the search honest.
• Own the deterministic scoring backbone: versioned scorers, shared and immutable experiment definitions, blind holdout discipline. Ensure results are comparable, auditable, and cumulative across the team rather than trapped in one person’s working directory.
• Expand the engine to new scoring and optimization domains across the business, including generosity and promotional spend, module placement and ranking, and search relevance.
• Bias toward interpretable strategies product partners can reason about, argue with, and implement without an external serving dependency.

Prove Ideas Before They Ship

• Mature our offline simulation environment so product hypotheses can be pre-screened against synthetic personas built from real behavioral data, before committing scarce live A/B capacity.
• Establish directional agreement between simulated and live outcomes as the credibility bar, and be honest with partners about where the simulation is and is not trustworthy.
• Drive adoption of simulation as a standard input to experiment prioritization with our product partners.

Turn Vision Into Work the Team Can Own

• Act as the Team’s technical lead: take strategic direction and decompose it into specs, skills, and tickets that individual engineers can own end to end without waiting on you.
• Set the working model for an AI-driven team. You define what a human specifies, what an agent builds, what a human reviews and raise the bar through code review, reusable patterns, and design review.
• Mentor engineers across the US and Romania pods, and write clearly, since not all collaboration is synchronous.
• Represent the team technically with partner engineering organizations, vendors, and external delivery partners on joint work.

THE STATS

• 8+ years of software, machine learning, or AI engineering experience, including technical leadership of a system other engineers built on.
• A track record of turning ambiguous business problems into measurable ones. Defining objectives, metrics, and guardrails alongside product partners rather than waiting to be handed a spec.
• Demonstrated breadth: credible in a technical design review, in a product prioritization conversation, and in front of senior stakeholders.
• Proven ability to decompose a vague strategic direction into workstreams that individual engineers can own autonomously.
• Expert-level Python in production settings: typing, testing, packaging, and performance awareness.
• Hands-on experience using agentic coding harnesses as real engineering tools, and designing the skills, context, tool access, and memory that make them effective.
• 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, plus hands-on work in a modern data platform such as Databricks.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent industry experience.
• Knowledge of sports and/or experience working within a heavily regulated industry is a plus.

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS

We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits, pet insurance, and more - check out all our benefits here: FanDuel Total Rewards . *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

The applicable salary range for this position is $159,000 - $208,950 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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