Engagement Manager

Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com. 

Turing Intelligence builds and ships production AI systems for large enterprises. In banking, capital markets, asset management and insurance, our clients come to us with a hypothesis about where AI can move a P&L line, and we turn it into working software that runs in their core workflows, in a regulated environment, with a measured result.

The Engagement Manager owns that outcome: from signed SOW through production deployment, adoption, and renewal. You are the client's day-to-day executive counterpart, the leader of a pod of Forward Deployed Engineers (FDEs), and the owner of the engagement's scope, timeline, margin, and expansion.

This is not a project-management seat and not an engineering seat. It is an account delivery leader who runs a book of business inside a client, keeps senior stakeholders confident, and holds the engagement to its commercial and delivery commitments. You will not write code, but you need enough technical fluency to scope AI work credibly, challenge your engineers' plans, and explain trade-offs to a client CTO or model-risk team without a translator.

Client relationship

• Be the trusted counterpart to client sponsors from working teams to managing directors and C-suite. Own the steering committee, the executive updates, and the hard conversations.
• Understand the client's business, org, and politics well enough to anticipate what they need before they ask, and to know which stakeholders can stall or accelerate an initiative.
•  Navigate regulated-enterprise complexity as part of the plan, not a surprise at go-live: model risk management, information security review, data residency, procurement, legal, and Responsible AI requirements.
• Protect the relationship through delivery problems. Bring bad news early, with a plan.

Delivery, SOW to production

• Own engagements end to end. Structure SOWs with clear scope, milestones, dependencies, acceptance criteria, and a value hypothesis before signature.
• Run the engagement: cadence, staffing, risk and dependency management, decision logs, client communications. Make real-time calls on scope and priority to protect the critical path.
•  Hold the standard that success is adoption and measured impact, not "delivered on time." Define the baseline and KPIs up front and report against them.
• Set the quality bar with your engineering lead: production readiness, evaluation of model-backed components, and acceptance testing are part of "done."

P&L and growth

• Own the engagement P&L against TI's revenue and margin targets. Manage staffing mix, utilization, change orders, and scope creep to protect gross margin. Forecast accurately and flag variance early.
• Identify and shape expansion: new use cases, adjacent business units, follow-on SOWs, renewals. Partner with the BFSI GM, who owns the account relationship and revenue number, to convert them.
• Report value delivered, risks, and key decisions to client sponsors and TI leadership on a fixed cadence.

Team leadership

• Lead a pod of FDEs and delivery staff. Set direction, unblock, and hold the bar on client-facing professionalism and delivery discipline.
• Partner with your technical lead on architecture and staffing decisions; own the outcome even where you don't own the design.
• Codify what works into reusable BFSI delivery playbooks, estimation models, and SOW patterns.

Required

• Collaborative Engagement Manager with sound leadership instincts, a team player who keeps teams motivated under delivery pressure and leads by example, serving as a role model in work ethic, accountability, and client commitment.
• 8+ years in client-facing delivery or consulting, with at least 3 years leading engagements or accounts for financial services clients (banking, capital markets, asset management, insurance, or payments).
•   Track record of owning engagement or account financials: margin, forecasting, staffing, change orders, renewals.
• You have led at least one AI, ML, or data-platform program into production at an enterprise and can speak to what the client changed as a result.
• Executive presence and relationship depth: you have run steering committees, managed MD-level sponsors, and retained accounts through difficult periods.
• Technical fluency: you can read an architecture diagram, understand how an LLM-based system is built and evaluated, and ask the questions that expose weak plans. You do not need to code.
•  Based in the New York metro area and able to be onsite with clients several days per week.

Preferred

• Engagement management at a technology consultancy, systems integrator, or AI-native delivery firm; or a delivery leadership role inside a bank or insurer's technology or data organization.
• Familiarity with BFSI regulatory context: model risk management, information security and third-party risk, data privacy and residency.
• Experience in a two-in-a-box model working alongside a commercial account owner.

• Two-in-a-box: you own delivery and engagement growth; the BFSI GM owns the account relationship and topline revenue.
• Small pods of senior FDEs staffed against outcomes, not seats.
• Bias to shipping. Iterative delivery and clarity over process.
•  Low ego. The outcome matters more than who gets the credit.

Values

• We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
  
  
• We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
  
  
• We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.

Advantages of joining Turing

• Work at the frontier of AI, helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.
  
  
• Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.
  
  
• Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges.
  
  
• Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.
  
  
• Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.

Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

For applicants from the European Union, please review Turing's GDPR notice here.