ai product manager

FE fundinfo

<div>FE fundinfo is a leading financial data provider, connecting the investment industry across the UK, Europe, and Asia-Pacific through an integrated platform. Our skilled team empowers clients with data-driven insights, making the industry Navigate Complexity with Confidence! We are currently recruiting for a Product Manager to join our team in UK.
We are hiring a new wave of product managers to lead AI-first pods, solving real customer problems at pace. You will not inherit a backlog. You will set direction, ship fast, and help pilot the future operating model for the whole product organisation.
Your key responsibilities as a AI Product Manager will be to:<ul><li>
Owning and driving the product roadmap for an AI‑first squad, delivering market‑leading AI‑powered solutions.
</li><li>Identifying, validating, and prioritising customer problems through research, interviews, and data‑driven insights.
</li><li>Translating product vision into clear requirements, delivery plans, and measurable success metrics.
</li><li>Working closely with engineering, data science, design, and commercial teams to deliver products end‑to‑end.
</li><li>Championing AI‑first ways of working and influencing stakeholders to embed AI adoption across the business.
</li><li>Successfully commercialising AI products in a B2B environment to deliver measurable customer and business value.</li></ul>
To join us as a AI Product Manager you will need the following experience and skills:<ul><li>
You will have a proven track record of building and launching AI‑driven products end‑to‑end.
</li><li>You will bring strong experience in B2B product management, including commercialising new solutions.
</li><li>You will have experience working in fast‑moving, agile squads or start‑up‑like environments.
</li><li>You will be highly skilled at uncovering customer needs and translating them into impactful product outcomes.
</li><li>You will demonstrate strong prioritisation, problem‑solving, decision‑making, and cross‑functional collaboration skills</li></ul>
Why this role:<ul><li>
Lead a pod with a clean sheet. This is not a BAU backlog. You will be handed real customer problems and the latitude to think fresh, set direction, and ship at pace. We are hiring product managers who want to lead, not coordinate.</li><li>
Shape an AI-first reimagining of the business. We are deep into reinventing how we serve clients and build products through an AI-first lens. Your pod is central to that work, not adjacent to it.</li><li>
Pilot the future operating model. How your pod runs becomes the template for how the whole product organisation runs. The work you do shapes the company, not just the roadmap.</li><li>
Real customers from day one. Investment managers, wealth platforms, and 3,900+ UK advice firms already use our products every day. No cold start, no waiting for adoption to arrive.</li><li>
Data others cannot replicate. 7m fund data points, 2m active portfolios, 550k+ regulatory documents a year, 75+ jurisdictions. What you build is genuinely differentiated because the inputs are.</li><li>
A mature business behind you. FE fundinfo is 30+ years old, 1,200+ people, profitable, and trusted across the industry. You can take ambitious bets without worrying about runway.</li><li>
A direct line to the people making the call. Senior leadership is hands-on with this transformation, not delegating it. Decisions move quickly and the work has real visibility.</li></ul>
By joining the team as a AI Product Manager, you will be offered the following:<ul><li>
25 days of annual leave with the option to buy an extra 5 days each year.</li><li>
Benefit from enhanced paternity, maternity, and shared parental leave.</li><li>
Secure your future with our pension scheme.</li><li>
Advance your career with sponsored learning and development, including formal qualifications.</li><li>
Private medical insurance as employee wellbeing matters</li><li>
Stay fit with discounted gym memberships.</li><li>
Take advantage of the Bike to Work scheme for eco-friendly commuting.</li><li>
Keep your eyes sharp with eye care and flu jab services.</li></ul> 
Apply today for immediate consideration and we will endeavour to get back to you within 5 working days. Visit our Glassdoor profile or fefundinfo.com to find out more about life @ FE fundinfo!</div>

AI Product Manager

Peak Health

<div>
 
 AI Product Manager
 
 
 
 PeakHealth &bull; SF Bay Area (3 days/week in office)
 
 
 
 
 
 
 The Mission
 
 
 
 We&rsquo;re rebuilding healthcare to keep people well. The American system is broken&mdash;built to treat illness, not prevent it.
 
 
 
 
 
 
 The Team
 
 
 
 Led by a repeat healthcare founder (2x unicorns / 1x IPO), you&rsquo;ll join a ~20-person team of top clinical, tech, and AI talent&mdash;including a 4x NYT bestselling Chief Medical Officer and a Founding Product Designer.
 
 
 
 
 
 
 What We Do
 
 
 
 PeakHealth is a new DTC care platform integrating women&rsquo;s health, longevity, and functional medicine into everyday primary care&mdash;with generative AI woven throughout.
 
 
 
 
 
 
 The Role
 
 
 
 You&rsquo;ll be our embedded product quality and execution PM, doing whatever needs to be done to make the product better and the team faster.
 
 
 
 
 
 
 
 Most of your time: poking around the product manually, finding bugs and UX issues, triaging incoming quality reports, and writing them up as LLM-readable specs so our engineers&rsquo; vibe coding agents can take a first pass at fixing them automatically. You&rsquo;re the human glue between &ldquo;something feels off&rdquo; and &ldquo;an agent shipped a fix.&rdquo;
 
 
 
 
 
 
 
 The rest of your time: owning smaller features end-to-end as product owner, supporting our clinical team, running light data analyses, and absorbing whatever startup ops needs doing. Larger roadmap and strategy stays with the founders for now.
 
 
 
 
 
 
 You Bring
 
 <ul>
 <li>
 
 1&ndash;4 years of product, product ops, APM, or adjacent experience.
 
 </li>
 <li>
 
 Experience at an early-stage startup, or a notably scrappy team inside a mid-stage one.
 
 </li>
 <li>
 
 An obsessive eye for product quality&mdash;you can use a product for 10 minutes and produce a 20-item issue list.
 
 </li>
 <li>
 
 Real fluency with modern AI tools (Cursor, Claude, ChatGPT, etc.) and the instinct to write bug reports as agent-ready prompts, not Jira tickets.
 
 </li>
 <li>
 
 A &ldquo;unicorn&rdquo; mentality: high autonomy, sharp critical thinking, zero attachment to title or scope boundaries.
 
 </li>
 <li>
 
 Comfort owning small features end-to-end&mdash;spec to shipped.
 
 </li>
 <li>
 Experience shipping AI-native product features that expose generative AI to end users.
 </li>
 <li>
 
 Startup business acumen&mdash;you can tell what&rsquo;s worth fixing now vs. what can wait.
 
 </li>
 </ul>
 
 
 
 
 Bonus Points
 
 <ul>
 <li>
 
 Direct experience at a close competitor in DTC longevity, weight loss / GLP-1, hormone health, women&rsquo;s health, or telehealth.
 
 </li>
 <li>
 
 Background in QA, product operations, or customer-facing support engineering.
 
 </li>
 <li>
 
 Basic data analysis chops (SQL, spreadsheets, whatever)
 
 at an early-career product manager level.
 </li>
 <li>
 
 Some front-end coding ability, or comfort opening a PR yourself.
 
 </li>
 <li>
 
 Experience building and shipping with vibe-coding tools like Lovable, Replit, Claude Code, or Cursor
 
 </li>
 </ul>
 
 
 
 
 This Role Isn&rsquo;t for You If&hellip;
 
 <ul>
 <li>
 
 You&rsquo;re allergic to manual bug hunting, edge-case testing, and &ldquo;boring&rdquo; quality work.
 
 </li>
 <li>
 
 You&rsquo;re skeptical of AI tools, or you&rsquo;d rather write Jira tickets than agent-ready prompts.
 
 </li>
 <li>
 
 You&rsquo;ve only worked at large, well-resourced companies.
 
 </li>
 <li>
 
 You need a scoped brief and someone funneling work to you.
 
 </li>
 </ul>
 
 
 
 
 Comp &amp; Location
 
 
 
 Comp:
 
 
 Competitive salary + meaningful equity
 
 
 
 
 Location:
 
 
 SF Bay Area (3 days/week in office).
 
 
 
 
 
 
 
 
</div>

NiCE

<div><div>At NiCE, we don't limit our challenges. We challenge our limits. Always. We're ambitious. We're game changers. And we play to win. We set the highest standards and execute beyond them. And if you're like us, we can offer you the ultimate career opportunity that will light a fire within you.</div>
So, what's the role all about?

We are seeking a mission-driven AI Product Manager to help build ethical, high-impact AI solutions for the Public Safety and Justice sector. In this role, you will bridge the gap between complex machine learning capabilities and the real-world needs of first responders, 911 center personnel, legal professionals, and community stakeholders. You will help define products that improve emergency response times, streamline judicial workflows, and ensure AI is deployed responsibly in the public interest.

Key Responsibilities
<ul>
<li>Discovery &amp; Research: Conduct interviews with law enforcement, emergency dispatchers, or legal clerks to identify pain points that can be solved via AI (e.g., automated transcription, predictive resource allocation, or evidence management).</li>
<li>Feature Definition: Translate user needs into clear PRDs (Product Requirement Documents), user stories, and technical specifications for engineering and data science teams.</li>
</ul><ul><li>Strategic Market Intelligence:
<ul><li>Conduct regular competitive analysis of key players in the Public Safety and Security market(e.g., Motorola Solutions, Axon, Mark43) to identify feature gaps and market opportunities.</li>
<li>Perform &quot;gap analysis&quot; on competitor documentation and public APIs to inform our technical roadmap.</li>
</ul></li><li>AI Trend Monitoring:
<ul><li>Stay at the forefront of AI breakthroughs, specifically monitoring advancements in Generative AI for casework, computer vision for weapon detection, and Drone as First Responder (DFR)</li>
<li>Evaluate how new models (e.g., from OpenAI or Anthropic) can be integrated into public safety &amp; Justice workflows responsibly.</li>
</ul></li></ul><ul><li>Roadmap Support: Help prioritize the product backlog based on impact, technical feasibility, and the unique regulatory constraints of the justice system.</li>
</ul>
Required Qualifications
<ul>
<li>Education: Bachelor's degree in Computer Science, Data Science, or a related field.</li>
<li>Experience:</li>
<li><ul><li>3-5 years of experience in delivering SaaS related offerings to market</li>
<li>1-3 years of experience in working with Generative AI technologies</li>
</ul></li><li>Technical Literacy: A foundational understanding of the ML lifecycle (data labeling, training, testing, and deployment).</li>
<li>Analytical Mindset: Ability to use data to justify product decisions and measure success through KPIs like model accuracy vs. human-in-the-loop efficiency.</li>
<li>Communication: Exceptional ability to synthesize complex technical trends into actionable business insights.</li>
</ul>
Preferred Skills
<ul>
<li>Understanding of the Public Safety and Justice markets(CAD/RMS systems, Case Management Systems, Body-Worn Cameras, Digital Evidence Management).</li>
</ul><ul><li>Experience with LLMs (Large Language Models) or Computer Vision.</li>
<li>Knowledge of data privacy laws and ethical AI frameworks.</li>
</ul>
Why Join Us? 
You will be at the forefront of a technological revolution in the public sector, creating tools that don't just drive profit, but actively save lives and ensure a fairer justice system.

What's in it for you?

Join an ever-growing, market-disrupting, global company where the teams &ndash; comprised of the best of the best &ndash; work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NICE-FLEX!
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 11275 
Reporting to: Director, Product Management 
Role Type: Individual Contributor

#LI-Hybrid<div> 
About NiCE
NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.</div></div>

Intent HQ

<div>About Intent HQ
Recognised by the Financial Times as one of the FT1000 Fast growing companies in Europe in 2022 and 2023, Intent HQ is a leader and innovator in Customer AI Analytics and Data Science with a blue chip international enterprise customer base and solid financial backing from our investors. Our mission is to become the world&rsquo;s preeminent Customer Intent platform by bringing together privacy-first signals intelligence, proprietary behavioural AI/ML analytics &amp; uniquely accessible enterprise insights into a single platform that organisations will use to build more genuine, sustainable and profitable relationships with their customers. . Our initial focus solved problems for clients in the telecommunications sector, including Verizon &amp; Orange. We have since expanded into the Financial Services, Retail and Social Media sectors including HB Reavis and Zurich Group as clients to name a few.
Our clients typically have tens of millions of customers and billions of interaction events each day. We have developed our platform to handle data at this enormous scale efficiently. Intent HQ is unique because we've focused on understanding customer interaction data. We do the hard-specialised work leaving our clients free to focus on integrating the insight into their business, with one Client seeing an additional &pound;26m annual revenue as a result of using our products and services.
Intent HQ is an exciting place to work, we are very proud to have made our debut on the FT1000 Fastest Growing Companies in Europe for 2022! We have a talented team of circa 100 -people (and growing!) based in &amp; around London, Barcelona, Lisbon and New York &amp; Tel Aviv, collectively speaking over 15 languages!<h4 class="jobSectionHeader">
Why Join Us:</h4><ul><li>
Exciting Work Environment: Work on cutting-edge technology at the intersection of AI and data analytics.</li><li>
Growth Opportunities: Advance your career in a fast-paced, innovative industry.</li><li>
Hybrid working: Based in our London office 2-3 days per week and the rest of the week remote, depending on location to the office</li></ul> 
Role Context
This role sits within the Product &amp; Tech organisation at Intent and partners closely with Data Science, Engineering, Client Services (to design and maintain quality standards) and other Product Managers.
IntentAI is the inference layer that turns raw behavioural and device signals into the brands, topics, moments and, eventually, forward-looking predictions (move, buy, churn) that make IntentOne valuable. IntentAI includes an Intent Semantic Layer that selects the right context for each goal and agent at scale, and is our core technical moat.
Today that moat is real but under-explained. This role owns that gap: setting the model north star, raising the bar on model quality and measurement, and making the intelligence legible to buyers, sellers, and the team. 
Role Summary
This role is responsible for:<ul><li>
Owning the product roadmap and north star for IntentAI: what our models predict, how good they need to be, and how that quality compounds into commercial value.</li><li>
Harmonising the Intent Semantic Layer across device and cloud signals, so behaviour captured on the device and in the cloud resolves into one consistent, trustworthy view of human context.</li><li>
Setting and operationalising the quality bar for models and enrichments (coverage, precision, recall, lift, freshness, drift, and cost at scale) so model performance is measured, visible, and improving. This role will be heavily data- and metric-driven.</li><li>
Owning the product story of the semantic layer: explaining clearly why it is differentiated, how it makes sense of human context against a goal, and why it is hard to replicate.</li><li>
Translating model and signal capability into outputs customers trust, with explainability and confidence built in rather than bolted on.</li><li>
Partnering with Data Science and Engineering to prioritise the model roadmap, close evaluation and monitoring gaps, and turn research into shipped, reliable product.</li></ul>
Core Responsibilities<ul><li>
Own the model north star and vision</li></ul><ul><li>
Define what &ldquo;good&rdquo; looks like across the model portfolio (brand and topic affinity, intent segments, moments of need, propensity and churn), with a clear understanding of how it ladders to customer ROI.</li><li>
Maintain a prioritised model roadmap grounded in commercial impact, not research novelty, and make the hard calls on where signal and model depth create real advantage.</li><li>
Articulate a durable vision for how the intelligence layer compounds, with better signals and scale driving better models at lower unit cost.</li><li>
Raise and operationalise model quality</li></ul><ul><li>
Set the evaluation standard for inference quality, coverage, cost, and scalability, measured by lift, precision, recall, and proxy outcomes against ground truth and in-market results.</li><li>
Work with QA to close known gaps in evaluation, drift detection, and performance monitoring so quality is continuously observed, not discovered in incidents.</li><li>
Define maturity indicators, confidence thresholds, and suppression rules so we never ship outputs that are misleading or unexplained.</li><li>
Explain the intent semantic layer</li></ul><ul><li>
Own clear, layered explanations of the semantic layer for technical and non-technical audiences, covering how it harmonises device and cloud signals, selects relevant context per goal, and keeps the platform accurate and cost-efficient at billions of events.</li><li>
Turn the moat into language Sales and Solutions can use to connect the smarts of the platform to the customer promise, without overstating what the evidence supports.</li><li>
Make outputs trustworthy</li></ul><ul><li>
Ensure outputs are grounded in model evidence, with explainable scoring and clear confidence, so enterprise buyers trust how they are generated and how their own rules are handled, removing the &ldquo;black box&rdquo; objection.</li><li>
Translate model needs into clear product requirements and reusable platform capability with Data Science and Engineering, and own the tradeoffs across model richness, latency, cost, and time-to-value.</li></ul>
What you&rsquo;ll bring<ul><li>
Deep fluency across the modelling stack, from supervised learning, propensity and uplift, to representation and embedding models, alongside modern LLM-based systems. You understand how predictive models are trained, evaluated, and shipped, not just prompted.</li><li>
A metrics-first instinct: fluent in precision, recall, lift, AUC, drift, and the economics of running models at scale. You explain complex intelligence simply and hold a high bar without stalling delivery.</li><li>
An exceptional flair for data translation and storytelling. You can turn complex models, signals, and analytical outputs into clear, compelling narratives that make the intelligence intuitive, credible, and actionable for technical and non-technical audiences alike.</li></ul> 
Diversity &amp; Inclusion
Intent HQ is an equal opportunities employer with an ethos of commitment to promoting and practicing diversity, equality and inclusion at work. At IHQ, different perspectives, ideas and experiences are valued and respected, with fair and equal opportunities provided for all. Our diversity and inclusion efforts have been recognised with us winning two consecutive Women in Tech UK Awards, under the Best Tech Employer (51-149 Employees)&rsquo; category &amp; being shortlisted for the Best Employer for Parental Support award - an achievement we are very proud of. This year in 2026 our Global Head if Talent is on the judges panel for the awards as we continue to sup such an important initiative.
Our Culture
Working for Intent HQ, you have the opportunity to work with cutting edge technology in an environment where you are encouraged to think and act outside traditional methods. We are a growing business with a flat structure meaning everyone is visible and able to make an impact, not just in their own role, but across the business on a daily basis. We promote a collaborative, innovative and sociable culture, oriented towards performance and competitive advantage. Our DNA is made up of flexibility to all staff with a family friendly approach and focus on personal development. We have high expectations and pride ourselves on our cultural standards. 
Benefits<ul><li>
Private Medical Insurance (subject to eligibility)</li><li>
Income Protection with Employee Assistance Programme (EAP)</li><li>
Life Assurance</li><li>
Higher than statutory maternity &amp; paternity benefits</li><li>
Pension scheme</li><li>
Flexible working</li><li>
26 days holiday (increasing with service)</li><li>
Tech pack</li><li>
Training opportunities</li><li>
Wellbeing programme</li><li>
Oliva mental health platform &amp; counselling</li><li>
Cycle to Work scheme</li><li>
Free access to onsite gym (including towel-serviced changing rooms and showers)</li><li>
Free breakfast daily &amp; healthy weekly lunch (when in office)</li></ul></div>

SAIC

<div>Job ID: 2614161
Location: Hanover, MD, US
Date Posted: 2026-06-30
Category: Engineering and Sciences
Subcategory: Systems Engineer
Schedule: Full-Time
Shift: Day Job
Travel: No
Minimum Clearance Required: TS.SCI_wPoly
Clearance Level Must Be Able to Obtain: TS/SCI with Poly
Potential for Remote Work: ORA_ON_SITE 
Description
Varen, an SAIC Company is seeking an AI Product Manager - SETA to join our team. This position is located in Hanover, MD and requires a TS/SCI with polygraph.

We are seeking an AI Product Manager - SETA to provide strategic and operational guidance to teams developing AI-enabled solutions. This role is suited for an experienced product-oriented professional who can help shape priorities, align stakeholders, drive disciplined execution, and keep technical efforts focused on mission value. This individual does not need to be a software engineer, but should possess strong technical fluency and enough AI literacy to engage credibly with engineers, data scientists, platform teams, and government leadership. The ideal candidate understands how to translate mission needs into executable plans, keep complex efforts on track, and identify when programs are drifting from useful outcomes. Above all, we want someone with authentic curiosity and passion&mdash;someone who actively studies the AI landscape, learns continuously, and brings informed perspective to a fast-changing field.

Key Responsibilities:
<ul>
<li>Provide SETA advisory support to government leadership and technical teams on AI product strategy, planning, and execution.</li>
<li>Help define and refine AI use cases, product goals, success criteria, priorities, and delivery roadmaps.</li>
<li>Guide teams in aligning AI solution development with mission outcomes, user needs, operational constraints, and program objectives.</li>
<li>Monitor effort execution and help keep teams on track with milestones, dependencies, risks, and decision points.</li>
<li>Support requirements development, backlog shaping, capability prioritization, and stakeholder coordination.</li>
<li>Translate between technical teams and non-technical leadership, ensuring shared understanding of what is being built, why it matters, and what risks exist.</li>
<li>Advise on AI adoption challenges, including scope control, change management, user trust, operational fit, and realistic implementation sequencing.</li>
<li>Review proposed AI solutions for feasibility, mission relevance, and alignment with available resources and timelines.</li>
<li>Support briefings, planning artifacts, concept papers, product documentation, and executive communications.</li>
<li>Help identify when teams need course correction, sharper problem framing, better metrics, or more disciplined execution.</li>
</ul>
Qualifications
<ul><li>Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience</li><li>
Bachelor&rsquo;s degree in a relevant field such as Business, Engineering, Computer Science, Information Systems, Operations, or related discipline.</li><li>
Experience in product management, technical program support, capability delivery, or requirements management in a government, defense, or complex enterprise environment.</li><li>
Demonstrated ability to work with technical teams building software, data, AI, or digital solutions.</li><li>
Strong understanding of product lifecycle concepts, roadmap planning, prioritization, stakeholder management, and execution tracking.</li><li>
Familiarity with AI concepts, terminology, current capabilities, and practical implementation challenges.</li><li>
Ability to advise leadership while also engaging productively with engineers and solution teams.</li><li>
Excellent written, verbal, and briefing skills.</li><li>
TS/SCI with polygraph</li></ul>
Target salary range: $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.</div>

AI Product Manager - SETA

<div>Director, Applied AI Product Manager 
At BNY, our culture allows us to run our company better and enables employees&rsquo; 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&rsquo;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 &ndash; and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. 
We&rsquo;re seeking a future team member for the role of Director, Applied AI Product Manager to join our EMEA Innovation / Strategic Partnerships, Investments &amp; Innovation team. This role is located in London, UK. 
In this role, you&rsquo;ll make an impact in the following ways:
Product strategy and opportunity framing
Define product vision, strategy, and roadmap for AI-enabled transformation opportunities.
Translate complex business or client problems into clear opportunity statements, product hypotheses, MVP scopes, PRDs, and execution plans.
Identify high-value opportunities for AI, intelligent automation, LLMs, workflow redesign, decision intelligence, and agentic solutions.
Partner with business sponsors, designers, AI Hub, engineering, data, risk, and platform teams to shape solutions that are valuable, feasible, usable, and governable.
Help convert discovery outputs into prioritised product opportunities, build paths, or handoff recommendations.
AI-enabled product development
Shape AI-enabled workflows, agent concepts, decision-support tools, prototypes, and product solutions.
Define what should be automated, augmented, escalated, or kept human led.
Work with technical partners to define orchestration needs, data requirements, permissions, integration considerations, model behaviour, and evaluation needs.
Use approved AI tools and methods to accelerate research, synthesis, product thinking, requirements development, prototyping, and decision support.
Critically evaluate AI outputs for quality, accuracy, bias, limitations, risk, and fitness for purpose.
Delivery, experimentation, and measurable outcomes
Lead cross-functional delivery from opportunity framing through prototype, MVP, pilot, or handoff.
Establish clear success metrics linked to productivity, operational efficiency, risk reduction, adoption, client experience, revenue support, or decision quality.
Drive fast learning loops through hypothesis testing, experimentation, user feedback, and evidence-based prioritisation.
Balance speed with control, ensuring responsible AI, data, compliance, security, operational resilience, and risk considerations are embedded early.
Create executive-ready narratives, decision packs, and product artefacts that support senior stakeholder alignment.
Stakeholder and team leadership
Partner with senior stakeholders across business lines, operations, technology, design, risk, compliance, and commercial teams.
Communicate complex AI and product concepts in clear, practical, outcome-focused language.
Work fluidly in small multidisciplinary teams, contributing beyond narrow role boundaries while maintaining clear accountability.
Mentor and support colleagues as the team builds stronger AI product capability.
Help create a team culture built on trust, constructive challenge, continuous learning, and shared ownership of outcomes. 
To be successful in this role, we&rsquo;re seeking the following:
Significant experience in AI product management, digital product management, enterprise product development, AI-enabled transformation, or technology-led business change.
Strong understanding of generative AI, LLM-enabled systems, intelligent automation, agentic workflows, and AI-enabled product capabilities.
Experience translating complex business problems into product strategies, requirements, roadmaps, prototypes, or delivery plans.
Ability to work with engineering, data science, AI Hub, design, business, and risk teams to shape practical solutions.
Strong understanding of enterprise technology concepts such as APIs, workflows, data flows, permissions, integration layers, observability, and production-readiness.
Experience operating in complex, regulated, or highly governed environments.
Strong stakeholder management, executive communication, prioritisation, and delivery leadership skills.
Ability to define and measure outcomes, not just deliver outputs.
<ul><li>We are looking for people who can thrive in a fast-moving, AI-enabled, high-trust team environment. The strongest candidates will be:
</li></ul>Comfortable with ambiguity and able to create structure without waiting for perfect framing.
Curious, self-directed, and able to learn new domains quickly.
Collaborative and team-oriented, with a willingness to build on others&rsquo; ideas and adapt when evidence changes.
Confident giving and receiving constructive feedback across all levels.
Resilient under pace, feedback, uncertainty, and changing priorities.
Strong communicators who can explain decisions, trade-offs, and risks clearly.
Evidence-led rather than opinion-led.
Risk-aware without being risk-averse.
Excited by continuous learning and willing to help others develop.
Comfortable operating across product, design, AI, data, engineering, risk, and business strategy.
Experience building or scaling AI-enabled products, internal platforms, workflow tools, agents, or automation capabilities.
Experience with AI product evaluation, model performance, responsible AI, prompt design, RAG, knowledge graphs, or agent orchestration.
Experience in financial services, capital markets, asset servicing, banking, payments, operations, risk, compliance, or data-intensive enterprise environments.
Experience working in innovation, venture-building, consulting, transformation, or emerging technology teams.
Product certifications, agile certifications, AI specialisations, or advanced degrees are helpful but not required where equivalent experience is demonstrated. 
At BNY, our culture speaks for itself, check out the latest BNY news at:
BNY Newsroom
BNY LinkedIn 
Here&rsquo;s a few of our recent awards:
<ul><li>America&rsquo;s Most Innovative Companies, Fortune, 2025
</li><li>World&rsquo;s Most Admired Companies, Fortune 2025
</li>&ldquo;Most Just Companies&rdquo;, Just Capital and CNBC, 2025 
<li>
</li></ul>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&rsquo;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.</div>

Director, Applied AI Product Manager

SSC HR Solutions

<div>
 
 Role Summary
 
 
 
 our company is hiring an
 
 AI Product Manager
 
 to own the operational line of the Technology team - task assignment, delivery cadence, performance tracking, documentation, and discipline - while keeping AI product delivery on track. This role runs the day-to-day engine of the team so engineers and data scientists can focus on building. The technical/architecture direction stays with the Technical Head; this role partners with that line but owns how work is planned, tracked, and shipped.
 
 
 The role combines
 
 understanding stakeholder requirements and leading client technical meetings
 
 , a
 
 hands-on understanding of how AI systems are deployed and how AI products are managed
 
 , and a
 
 research mandate to advance D proprietary models and agentic layers
 
 . These capabilities matter far more than years on a CV, which is why we are opening this at a mid-level (2-5 years) for a sharp, client-facing operator who can grow with the company.
 
 
 <ul>
 <li>
 Core Competencies
 
 
 </li>
 </ul>
 Candidates will be assessed against the following areas:
 
 
 <li>
 Stakeholder requirements &amp; client technical meetings - leads client and stakeholder technical meetings with confidence, asks the right questions to surface real needs and constraints, captures and documents requirements clearly, translates them into specs and tasks for the team, and manages expectations and scope throughout delivery. Comfortable being the technical face of in front of clients
 </li>
 <li>
 AI systems deployment - practical understanding of the AI/ML delivery lifecycle: moving models and AI features from prototype to production, MLOps basics (versioning, retraining, monitoring, rollback), data pipelines, evaluation, and the operational risks of running AI in production. Able to spot delivery blockers early and hold an engineering team accountable to a deployment plan
 </li>
 <li>
 AI product management - translating business goals into a prioritised backlog, writing clear specs and acceptance criteria, running an analysis-before-development workflow, managing scope against client commitments, and owning roadmap, releases, and stakeholder communication for AI products
 </li>
 <li>
 Applied AI research direction - able to read the landscape of models and agentic techniques, frame research objectives, and steer the team toward greater in-house capability - reducing dependence on third-party models and building proprietary models and agentic layers into our company AI systems
 </li>
 <li>
 Key Responsibilities
 </li>
 <li>
 Stakeholder requirements &amp; client meetings
 </li>
 <li>
 lead client and stakeholder technical meetings, elicit and document requirements, translate them into clear specs and tasks, manage scope and expectations, and act as the technical point of contact between the client, leadership, and the team
 </li>
 <li>
 Team &amp; operations management
 </li>
 <li>
 assign and balance work across the Technology team, run the weekly delivery cadence, remove blockers, and own team discipline and ways of working
 </li>
 <li>
 Delivery &amp; product ownership
 </li>
 <li>
 maintain the backlog and roadmap for the Paula and -Hub products, enforce the analysis-before-development workflow, and ensure no client commitments are made without proper scoping
 </li>
 <li>
 Research &amp; proprietary capability
 </li>
 <li>
 set and drive research objectives to grow own models and agentic layers, run a pipeline of experiments alongside delivery, and progressively move the AI systems from off-the-shelf components toward proprietary, in-house capability
 </li>
 <li>
 Performance &amp; KPIs
 </li>
 <li>
 track weekly KPIs, run progress reviews, evaluate performance, and surface risks to leadership early
 </li>
 <li>
 Documentation &amp; process
 </li>
 <li>
 ensure all work is documented and stored in the shared knowledge base, keep process living and followed, and onboard new joiners into it
 </li>
 <li>
 Meeting cadence
 </li>
 run the standing weekly structure (e.g. Career Hub, client, and planning sessions) and keep them focused and outcome-driven.
 <li>
 Tools &amp; Ways of Working - AI-Assisted Operations
 
 
 </li>
 our company runs its team operations with AI assistants (
 
 Cowork-style skills/agents
 
 ) connected directly to the tools the team lives in. The AI Product Manager is expected to use and improve this setup to run the team in the most efficient way, including:
 
 
 <ul>
 <li>
 ClickUp (mandatory) - AI-assisted task creation, assignment, status sync, and KPI/progress reporting; ClickUp is the single source of truth for all work
 </li>
 <li>
 Documents (Google Drive / knowledge base) - AI-assisted drafting, organising, and retrieval of specs, processes, meeting notes, and deliverables; all documentation lives in the shared drive
 </li>
 <li>
 Code repository - connected read access to the repo to track delivery progress, link work items to commits/PRs, and keep product status grounded in what is actually shipping
 
 
 </li>
 </ul>
 Comfort with AI/agentic tooling to automate routine operations (status roll-ups, reminders, reporting, document generation) is a core part of the job, not a bonus.
 
 
 
 Requirements
 
 
 
 
 
 Required Qualifications
 
 
 
 
 <ul>
 <li>
 2 - 5 years in technical product management, AI/ML product or delivery management, technical operations, or team lead roles within a software / AI / data environment
 </li>
 <li>
 Experience leading client / stakeholder technical meetings and gathering and documenting requirements
 </li>
 <li>
 Demonstrated understanding of AI systems deployment and AI product management
 </li>
 <li>
 Awareness of current models, agentic frameworks, and the build-vs-buy trade-offs for AI capability
 </li>
 <li>
 Hands-on experience running a work-management tool (ClickUp, Jira, Linear, Asana, or similar) for a delivery team
 </li>
 <li>
 Strong organisation, written communication, and stakeholder-management skills; fluent English and Arabic
 </li>
 <li>
 Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
 </li>
 <li>
 Nice to Have
 </li>
 <li>
 Exposure to MLOps tooling, cloud platforms, or data-pipeline orchestration
 </li>
 <li>
 Hands-on experience building or fine-tuning models, or designing agentic / multi-agent systems
 </li>
 <li>
 Experience building or customising AI/automation workflows (Cowork, agents, scripting, or no-code automation)
 </li>
 <li>
 Prior experience managing a client-facing product squad
 </li>
 <li>
 First 90 Days - Success Measures
 </li>
 <li>
 Trusted to run client technical meetings solo, with requirements captured and signed off clearly
 </li>
 <li>
 Fully owns the ClickUp board and weekly KPI reporting for both product squads
 </li>
 <li>
 A defined research roadmap for proprietary models and agentic layers, with first experiments under way
 </li>
 <li>
 Team operating process documented, followed, and kept current in the shared drive
 </li>
 <li>
 Predictable weekly delivery cadence with blockers surfaced and resolved early
 </li>
 <li>
 AI-assisted operations (reporting, reminders, documentation) running with minimal manual effort
 </li>
 </ul>
</div>

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