Product Owner – Operations & Controls Platform

About Turing:

Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies

About the Role:

We are looking for an experienced Product Owner to lead the strategy, roadmap, and execution for platforms supporting Back Office Operations and Global Business Finance. The ideal candidate brings strong product management experience combined with deep knowledge of financial operations, operational controls, and controller functions.

This role will partner closely with business stakeholders, engineering, and operations teams to modernize back-office platforms and improve operational efficiency. While familiarity with AI is important, the primary focus is on delivering business value through well-designed operational systems rather than building AI solutions.

Key Responsibilities:

• Own the product vision, roadmap, and prioritization for Operations \& Controls platforms.
• Lead product discovery by understanding business problems, operational workflows, and stakeholder requirements.
• Partner with Back Office Operations, Controllers, Finance, and Technology teams to improve operational processes.
• Drive modernization initiatives across reconciliation, financial controls, exception management, workflow automation, and operational reporting.
• Build and manage the product backlog, define user stories, and prioritize features based on business value.
• Coordinate delivery across engineering, architecture, and business stakeholders.
• Track milestones, dependencies, risks, and delivery progress.
• Promote transparency and effective stakeholder communication throughout the product lifecycle.
• Identify practical opportunities where AI and automation tools can improve productivity, decision-making, and operational efficiency.
• Ensure solutions meet governance, audit, and operational control requirements.

Required Qualifications:

• 7\+ years

of experience as a Product Owner, Product Manager, or Senior Business Analyst within Financial Services.

• Strong experience supporting

Back Office Operations, Controllers, Finance Operations, Treasury, or Investment Operations

.

• Experience with

cash reconciliation, position reconciliation, operational controls, controller workflows, or financial close processes

.

• Experience building or enhancing

corporate back-office platforms and operational systems

.

• Strong understanding of operational risk, controls, reconciliation processes, and governance.
• Excellent stakeholder management and cross-functional collaboration skills.
• Proven ability to manage product roadmaps, planning, prioritization, and execution.
• Strong analytical, communication, and problem-solving skills.
• Familiarity with AI tools (e.g., ChatGPT, Copilot, Gemini) and understanding of where AI can improve operational workflows. Hands-on AI solution development is not required.
• Ability to work effectively with engineering teams and understand modern software delivery practices.

Nice to Have:

• Experience with platforms such as

Geneva, Arcesium, Investran, Kyriba

, or similar fund accounting and operations systems.

• Experience working with fund administrators or investment operations teams.
• Background in treasury, controller organizations, finance transformation, or operations transformation.
• Experience with Agile product delivery.
• Exposure to workflow automation, cloud platforms, or modern enterprise applications.

Ideal Candidate Profile:

The ideal candidate has experience leading products for

finance or operations organizations

, understands how

controllers and back-office teams operate

, and can translate business needs into scalable product solutions. They are comfortable working with AI-enabled tools and understand where AI can add value but are

not required to have built AI products or machine learning solutions

.