AI Product Engineer Jobs in Pittsburgh, PA
AI Product Engineer jobs in Pittsburgh are concentrated across Oakland, Shadyside, and the Strip District, with strong demand from tech, healthcare AI, and robotics sectors. Employers hiring right now include Google, BNY, and EXL. Find a role that fits below and apply directly.
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AI Security Product Manager
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.
We are seeking an AI Security Product Manager to lead the strategy, roadmap, and execution of security capabilities that enable safe, scalable adoption of AI across the enterprise. This role sits at the intersection of product management, cybersecurity, engineering, and architecture , translating emerging AI security risks into practical platform capabilities, controls, and operating processes. This role is in Pittsburgh PA or Lake Mary, FL
The ideal candidate brings a strong product mindset, along with prior experience in engineering and architecture , and can define product direction for capabilities such as AI governance tooling, model and agent security controls, prompt and data protection, AI observability, policy enforcement, identity and access controls, and secure AI lifecycle workflows . This person must be able to work across technical and non-technical stakeholders, prioritize high-impact outcomes, and drive delivery in a complex enterprise environment.
Key Responsibilities
- Define and own the product vision, strategy, and roadmap for AI security capabilities across the enterprise.
- Translate AI security risks, regulatory expectations, and control requirements into product requirements and prioritized backlog items.
- Partner with cybersecurity, engineering, architecture, data, legal, risk, and governance teams to deliver secure-by-design AI capabilities.
- Drive product development for controls supporting AI platforms, agents, model integrations, and related workflows.
- Use prior engineering and architecture experience to shape practical, scalable, and technically credible product requirements.
- Shape requirements for areas such as:
- AI application and agent security
- Model access governance
- Prompt and data protection
- AI activity logging and observability
- Policy enforcement and runtime guardrails
- Identity, authorization, and least privilege controls
- Third-party AI risk management
- Develop business cases, success metrics, and adoption plans for new AI security capabilities.
- Prioritize features and investments based on risk reduction, enterprise value, technical feasibility, and adoption needs.
- Create clear product requirements, user stories, acceptance criteria, and rollout plans.
- Lead cross-functional execution from concept through pilot, launch, and scale.
- Establish feedback loops with users, security teams, and platform teams to continuously improve product effectiveness.
- Track external market developments, regulatory changes, and emerging threats relevant to AI security.
- Communicate roadmap progress, decisions, dependencies, and risks to senior stakeholders in a concise, decision-ready manner.
Qualifications
- 10+ years of experience across product management, engineering, architecture, cybersecurity, enterprise technology, or related fields .
- Former hands-on experience in engineering and architecture roles, with the ability to engage credibly with technical teams and influence solution direction.
- Experience working in or alongside cybersecurity, cloud, identity, developer platform, or governance functions.
- Strong understanding of AI/ML and GenAI concepts, with the ability to translate technical and risk concepts into product strategy.
- Experience defining product roadmaps and delivering complex enterprise products across multiple stakeholder groups.
- Strong ability to write product requirements and convert ambiguity into clear execution plans.
- Familiarity with AI security concepts such as:
- prompt injection and misuse risks
- model and agent access controls
- human-in-the-loop and approval patterns
- logging, monitoring, and traceability
- Third-party model and vendor risk
- Excellent communication and stakeholder management skills.
- Ability to operate effectively in a fast-moving, highly cross-functional environment.
Preferred Qualifications
- Experience in AI security, cloud security, identity and access management, application security, or security architecture.
- Experience with enterprise AI platforms, AI governance processes, or model risk/control frameworks.
- Familiarity with secure SDLC, platform security patterns, and policy/control implementation.
- Experience working with regulated environments and audit or compliance stakeholders.
- Demonstrated ability to launch 0-to-1 or early-stage enterprise security capabilities.
Success Profile
The successful candidate will:
- Bring clarity to a fast-evolving AI security landscape.
- Balance speed, usability, and control effectiveness.
- Influence across organizational boundaries without relying solely on formal authority.
- Convert risk themes into practical products and measurable outcomes.
- Apply engineering and architecture experience to ensure product direction is implementable, scalable, and aligned to enterprise realities.
- Drive execution with discipline while keeping long-term platform strategy in view.
Example Outcome Areas
- Launch governance-enabling product features that improve secure onboarding of AI use cases.
- Improve visibility into AI usage, data flows, and security-relevant activity.
- Reduce risk from overprivileged agents, unmanaged integrations, or weak authorization models.
- Introduce scalable control patterns for AI applications and services.
- Support enterprise adoption of AI by making security requirements more usable, measurable, and operationally efficient.
At BNY, our culture speaks for itself, check out the latest BNY news at:
BNY Newsroom
BNY LinkedIn
Here’s a few of our recent awards:
America’s Most Innovative Companies, Fortune, 2025
World’s Most Admired Companies, Fortune 2025
“Most Just Companies”, Just Capital and CNBC, 2025
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans..
See All 36 AI Product Engineer Jobs in Pittsburgh
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Find AI Product Engineer JobsAI Product Engineer Job Market in Pittsburgh
Who's Hiring
- Google11

- BNY7

- EXL4

- Aires4

- Expedient4

Top Industries Hiring
- Transportation & Logistics
AI Product Engineer Jobs in Pittsburgh: Frequently Asked Questions
How do I get a ai product engineer job in Pittsburgh?
Focus on Pittsburgh's strongest hiring pockets: university-adjacent tech in Oakland, healthtech and clinical AI firms in the medical corridor, and robotics and autonomous systems companies in the Strip District and Lawrenceville. Candidates who can show hands-on experience building or shipping AI-powered products, not just modeling work, stand out most here. Targeting Pittsburgh's dense cluster of mid-size AI startups alongside established research-commercialization spinouts gives you the broadest set of realistic openings.
Which companies hire ai product engineers in Pittsburgh?
Pittsburgh ai product engineer roles are posted by Google, BNY, and EXL and others right now, based on current listings on Migrate Mate as of September 2026. The city's employer mix leans heavily toward healthtech firms, autonomous vehicle and robotics companies, and university spinouts commercializing research from Carnegie Mellon and the University of Pittsburgh.
Are there remote ai product engineer jobs in Pittsburgh?
Yes, though ai product engineering is more remote-friendly for product strategy, roadmapping, and cross-functional coordination work than for roles requiring close collaboration with embedded hardware or lab teams. About 100% of ai product engineer openings tied to Pittsburgh are remote or hybrid as of September 2026, reflecting strong demand from the city's software and healthtech employers. Robotics-adjacent roles in Pittsburgh tend to require more on-site presence than pure software AI positions.
How can I get a ai product engineer job in Pittsburgh with little or no experience?
The most realistic entry path in Pittsburgh is targeting associate product or AI solutions roles at mid-size healthtech and software companies, which hire more junior talent than the city's larger autonomous systems firms. Carnegie Mellon's continuing education programs and the Pittsburgh startup ecosystem around Innovation Works frequently surface entry-level openings. Building a portfolio with small shipped AI features or contributing to open-source tooling used locally gives Pittsburgh hiring managers something concrete to evaluate when your formal experience is limited.
Which industries hire the most ai product engineers in Pittsburgh?
The sectors hiring the most ai product engineers in Pittsburgh are Transportation & Logistics, based on current listings on Migrate Mate as of September 2026. Pittsburgh's identity as a robotics and medical research hub means those sectors consistently generate the densest concentration of ai product engineering demand in the region.
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