AI Product Owner Jobs at Deloitte with Visa Sponsorship
Deloitte hires AI Product Owners to lead the build-out of enterprise AI solutions across its consulting practice, working at the intersection of technology strategy and client delivery. The firm has an established sponsorship infrastructure that supports international candidates across multiple visa categories for this function.
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Get Access To All JobsINTRODUCTION
Zora AI is Deloitte's AI agent platform delivering role-/function-specific products (e.g., Finance, Procurement, Supply Chain, Customer, Human Capital). As a Product Manager, you will own one or more sets of agent-enabled products end-to-end-defining vision, roadmap, requirements, and delivery-while ensuring trust, adoption, and measurable business outcomes for enterprise users.
Key Responsibilities:
- Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
- Translate needs into outcomes: Partner with clients/internal teams to identify high-value use cases, map workflows, and define "jobs to be done" and measurable success metrics.
- Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
- Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
- Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.
- Data and integration leadership: Drive requirements for connectors, data access patterns, security/privacy, logging/auditability, and integration with enterprise systems.
- Trustworthy AI & risk management: Partner with risk/compliance to address model governance, safety, monitoring, explainability, bias, and audit requirements.
- Go-to-market and enablement: Collaborate with sales and delivery to package offerings, define pricing/packaging inputs, create demos, and support pursuits and launches.
- Operate the product cadence: Maintain backlog, run sprint planning, track progress, and align stakeholders through clear decision points and communications.
Required Qualifications:
- 7+ years of Product Management experience (enterprise software, SaaS, platforms, or data products), including shipping products from concept to GA.
- 2+ years of recent experience delivering products involving AI/ML (GenAI preferred), including evaluation, monitoring, and iteration loops.
- 2+ years of recent experience supporting product discovery (research, hypothesis testing, experimentation) and product delivery (requirements, backlog, release management).
- 1+ year working with enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines).
- Limited immigration sponsorship may be available.
- Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
Preferred:
- Experience with agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns).
- Familiarity with LLM evaluation (quality metrics, red-teaming, grounding, hallucination mitigation) and observability.
- Domain depth in one or more target functions (e.g., Finance, Procurement, Supply Chain, HR, Customer Operations).
- Consulting, enterprise transformation, or platform product experience (shared services, reusable components, governance).
- Proven ability to manage multiple products with competing priorities and shared platform dependencies.
- Experience launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces.
- Excellent stakeholder management and executive communication; able to write crisp narratives, PRDs, and decision memos.
- Track record of partnering with engineering, design, data science, and risk/compliance teams to deliver in regulated or high-stakes environments.
Key Deliverables
- Product strategy and 12-18 month roadmap with measurable outcomes.
- PRDs, epics, user stories, and acceptance criteria for each product/agent capability.
- Use-case catalog and prioritization model (value, feasibility, risk, readiness).
- MVP/pilot plans with success metrics, rollout phases, and scale criteria.
- Trust & governance artifacts: evaluation approach, monitoring plan, audit/logging requirements, and risk controls (in partnership with risk teams).
- Release plans and launch readiness checklists (docs, training, demo scripts, enablement).
- Customer feedback loop: telemetry dashboards, VOC insights, and iteration plan.
How success will be measured (example outcomes)
- Adoption: active users, repeat usage, workflow completion rates, feature utilization by product set.
- Business impact: cycle-time reduction for targeted workflows, cost-to-serve reductions, improved forecast accuracy or exception resolution time (by use case).
- Quality & reliability: task success rate, low rework/rollback rates, latency/uptime targets, incident trends.
- Trust & compliance: audit readiness, policy adherence, reduction in high-severity model risks, successful governance reviews.
- Delivery excellence: roadmap predictability, on-time releases, stakeholder satisfaction, reduced dependency blockers.
- Customer outcomes: pilot-to-scale conversion, referenceable wins, renewal/expansion influence (where applicable).
Working model & stakeholders (edit as needed)
- Working model: Remote + Hybrid (2-3 days onsite) with flexibility based on team and client needs; operates in agile product teams with regular release cadence.
- Core stakeholders:
- Engineering (platform + product squads)
- Data Science / Applied AI (models, evaluation, tuning)
- Design / Research (UX, workflow design, prototyping)
- Cybersecurity & Privacy (security controls, data protection)
- Risk, Legal, Compliance (AI governance, auditability, policy alignment)
- Domain SMEs (Finance, Procurement, Supply Chain, HR, etc.)
- Sales, Alliances, and Delivery/Implementation (pursuits, packaging, rollout)
- Customer/Client stakeholders (product owners, process owners, IT, operations)
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $102,000 - $210,000.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
EA_ITS_ExpHire
INTRODUCTION
Zora AI is Deloitte's AI agent platform delivering role-/function-specific products (e.g., Finance, Procurement, Supply Chain, Customer, Human Capital). As a Product Manager, you will own one or more sets of agent-enabled products end-to-end-defining vision, roadmap, requirements, and delivery-while ensuring trust, adoption, and measurable business outcomes for enterprise users.
Key Responsibilities:
- Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
- Translate needs into outcomes: Partner with clients/internal teams to identify high-value use cases, map workflows, and define "jobs to be done" and measurable success metrics.
- Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
- Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
- Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.
- Data and integration leadership: Drive requirements for connectors, data access patterns, security/privacy, logging/auditability, and integration with enterprise systems.
- Trustworthy AI & risk management: Partner with risk/compliance to address model governance, safety, monitoring, explainability, bias, and audit requirements.
- Go-to-market and enablement: Collaborate with sales and delivery to package offerings, define pricing/packaging inputs, create demos, and support pursuits and launches.
- Operate the product cadence: Maintain backlog, run sprint planning, track progress, and align stakeholders through clear decision points and communications.
Required Qualifications:
- 7+ years of Product Management experience (enterprise software, SaaS, platforms, or data products), including shipping products from concept to GA.
- 2+ years of recent experience delivering products involving AI/ML (GenAI preferred), including evaluation, monitoring, and iteration loops.
- 2+ years of recent experience supporting product discovery (research, hypothesis testing, experimentation) and product delivery (requirements, backlog, release management).
- 1+ year working with enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines).
- Limited immigration sponsorship may be available.
- Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
Preferred:
- Experience with agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns).
- Familiarity with LLM evaluation (quality metrics, red-teaming, grounding, hallucination mitigation) and observability.
- Domain depth in one or more target functions (e.g., Finance, Procurement, Supply Chain, HR, Customer Operations).
- Consulting, enterprise transformation, or platform product experience (shared services, reusable components, governance).
- Proven ability to manage multiple products with competing priorities and shared platform dependencies.
- Experience launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces.
- Excellent stakeholder management and executive communication; able to write crisp narratives, PRDs, and decision memos.
- Track record of partnering with engineering, design, data science, and risk/compliance teams to deliver in regulated or high-stakes environments.
Key Deliverables
- Product strategy and 12-18 month roadmap with measurable outcomes.
- PRDs, epics, user stories, and acceptance criteria for each product/agent capability.
- Use-case catalog and prioritization model (value, feasibility, risk, readiness).
- MVP/pilot plans with success metrics, rollout phases, and scale criteria.
- Trust & governance artifacts: evaluation approach, monitoring plan, audit/logging requirements, and risk controls (in partnership with risk teams).
- Release plans and launch readiness checklists (docs, training, demo scripts, enablement).
- Customer feedback loop: telemetry dashboards, VOC insights, and iteration plan.
How success will be measured (example outcomes)
- Adoption: active users, repeat usage, workflow completion rates, feature utilization by product set.
- Business impact: cycle-time reduction for targeted workflows, cost-to-serve reductions, improved forecast accuracy or exception resolution time (by use case).
- Quality & reliability: task success rate, low rework/rollback rates, latency/uptime targets, incident trends.
- Trust & compliance: audit readiness, policy adherence, reduction in high-severity model risks, successful governance reviews.
- Delivery excellence: roadmap predictability, on-time releases, stakeholder satisfaction, reduced dependency blockers.
- Customer outcomes: pilot-to-scale conversion, referenceable wins, renewal/expansion influence (where applicable).
Working model & stakeholders (edit as needed)
- Working model: Remote + Hybrid (2-3 days onsite) with flexibility based on team and client needs; operates in agile product teams with regular release cadence.
- Core stakeholders:
- Engineering (platform + product squads)
- Data Science / Applied AI (models, evaluation, tuning)
- Design / Research (UX, workflow design, prototyping)
- Cybersecurity & Privacy (security controls, data protection)
- Risk, Legal, Compliance (AI governance, auditability, policy alignment)
- Domain SMEs (Finance, Procurement, Supply Chain, HR, etc.)
- Sales, Alliances, and Delivery/Implementation (pursuits, packaging, rollout)
- Customer/Client stakeholders (product owners, process owners, IT, operations)
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $102,000 - $210,000.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
EA_ITS_ExpHire
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Get Access To All JobsTips for Finding AI Product Owner Jobs at Deloitte Jobs
Frame your portfolio around consulting delivery outcomes
Deloitte evaluates AI Product Owners on client-facing impact, not just internal product metrics. Restructure your portfolio to highlight how you translated AI capabilities into measurable client outcomes, such as reduced cycle times or expanded product adoption across engagements.
Clarify your visa category with Deloitte early
Deloitte sponsors H-1B, H-1B1, and E-3 visas for this role. If you hold an Australian or Singapore passport, ask the recruiter about E-3 or H-1B1 eligibility upfront, since those tracks bypass the H-1B lottery entirely and can accelerate your start date.
Align your degree field to specialty occupation standards
USCIS requires that your degree field directly relates to the AI Product Owner role. A computer science, engineering, or information systems degree maps cleanly. A business degree without a technical concentration can draw USCIS scrutiny, so prepare supplementary documentation if your background is mixed.
Target Deloitte's AI and data practice specifically
Deloitte posts AI Product Owner roles across multiple practice areas, but the AI and Data practice runs the highest volume of these positions. Focusing your applications there puts you in front of hiring managers whose teams are actively structured around sponsored international talent.
Prepare for an October start when lottery applies
If your offer requires an H-1B cap-subject petition, USCIS's fiscal year cap means your employment can begin no earlier than October 1. Build this into your negotiations with Deloitte's talent team so contract terms and your current status timeline align before you accept.
Use Migrate Mate to surface open roles by visa type
Deloitte's AI Product Owner openings are distributed across practice lines and geographies, making them hard to track manually. Use Migrate Mate to filter and monitor these positions by sponsorship eligibility so you can prioritize applications before headcount closes.
AI Product Owner at Deloitte jobs are hiring across the US. Find yours.
Find AI Product Owner at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for AI Product Owners?
Yes, Deloitte sponsors H-1B visas for AI Product Owner roles. As a large professional services firm with a mature immigration program, Deloitte works with in-house immigration counsel to file cap-subject and cap-exempt petitions depending on your situation. If you're currently on OPT or a prior H-1B, the process and timeline will differ, so confirm your specific pathway with the recruiter early in the process.
How do I apply for AI Product Owner jobs at Deloitte?
You can apply directly through Deloitte's careers portal or browse open roles filtered by sponsorship eligibility on Migrate Mate. When applying, emphasize AI product delivery experience in consulting or enterprise environments, and be explicit in your application that you require sponsorship. Deloitte's recruiters screen for sponsorship need early, so transparency upfront avoids delays later in the process.
Which visa types does Deloitte commonly use for AI Product Owner roles?
Deloitte sponsors H-1B, H-1B1, and E-3 visas for this function, as well as supporting Green Card pathways through EB-2 and EB-3 classifications for long-term employees. Australian citizens are well-positioned to pursue the E-3 route, which has no lottery and allows unlimited two-year renewals. Singapore nationals may qualify for the H-1B1, which also bypasses the annual cap.
What qualifications does Deloitte expect for AI Product Owner roles?
Deloitte typically looks for candidates with a technical bachelor's degree or higher in computer science, engineering, or a related field, combined with hands-on experience managing AI or machine learning products through a full delivery lifecycle. For consulting-track roles, client-facing experience is weighted heavily. Familiarity with Agile frameworks, roadmap prioritization, and cross-functional stakeholder management in enterprise environments strengthens your candidacy significantly.
How long does the sponsorship and onboarding process take at Deloitte?
Timeline depends on visa type. E-3 and H-1B1 petitions can often be processed within a few weeks with consular appointments, while cap-subject H-1B petitions require registration in April with an October 1 start date at the earliest. USCIS premium processing, which expedites adjudication to roughly 15 business days, is available for I-129 petitions and Deloitte's immigration team can advise on whether it applies to your case.
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