AI Product Manager Jobs at Deloitte with Visa Sponsorship
Deloitte hires AI Product Managers across its technology and consulting practices, working on enterprise AI solutions for clients in every major industry. The firm has a well-established visa sponsorship program and regularly supports H-1B, E-3, and Green Card pathways for qualified candidates in this function.
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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

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 Manager Jobs at Deloitte Jobs
Frame your AI experience for consulting contexts
Deloitte's AI Product Manager roles sit inside client delivery teams, not internal product orgs. Emphasize experience translating AI capabilities into client-facing outcomes, not just shipping internal tools. Interviewers will probe for stakeholder management across ambiguous, multi-party engagements.
Align your credentials to specialty occupation standards
USCIS evaluates H-1B eligibility on whether the role requires a specific bachelor's degree or higher. For AI Product Manager positions, a degree in computer science, data science, or a related technical field strengthens your petition compared to a general business background.
Confirm your visa type fits Deloitte's sponsorship scope early
Deloitte sponsors H-1B, H-1B1, and E-3 visas, but each requires a separate petition and LCA filing with DOL. If you're Australian, confirm whether the recruiter is familiar with E-3 processing, since not all hiring managers handle it routinely.
Target open roles through Migrate Mate's verified job board
Deloitte posts AI Product Manager roles across multiple practice areas and geographies, making it easy to miss relevant openings. Use Migrate Mate to filter specifically for Deloitte roles that include visa sponsorship, so you're not sorting through positions with no sponsorship signal.
Build a case file before your offer conversation
Deloitte's immigration team initiates the LCA and I-129 filing after an offer is accepted. Having your educational transcripts, credential evaluations for non-U.S. degrees, and employment history documentation ready before that conversation shortens the filing timeline significantly.
Plan around the H-1B cap if you're on OPT or a student visa
If you're not already in H-1B status, Deloitte can only file during the annual April registration window, with employment starting no earlier than October 1. Discuss the cap timeline with your recruiter before signing an offer so your start date accounts for USCIS processing.
AI Product Manager at Deloitte jobs are hiring across the US. Find yours.
Find AI Product Manager at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for AI Product Managers?
Yes, Deloitte sponsors H-1B visas for AI Product Manager roles and is one of the more active professional services firms in this space. Sponsorship is handled through Deloitte's internal immigration team after an offer is extended. If you're subject to the H-1B cap, your start date will align with the October 1 fiscal year window following the April registration lottery.
How do I apply for AI Product Manager jobs at Deloitte?
Applications go through Deloitte's careers portal, where roles are listed by practice area and location. Filtering for AI or technology consulting roles narrows the results. You can also browse verified AI Product Manager openings at Deloitte that include sponsorship signals on Migrate Mate, which surfaces roles based on the firm's documented sponsorship history for this function.
Which visa types does Deloitte commonly use for AI Product Managers?
Deloitte sponsors H-1B, H-1B1, and E-3 visas for AI Product Manager positions, depending on your nationality. H-1B is the most common pathway for most international candidates. Australian citizens can pursue the E-3, which has no lottery and allows two-year renewable periods. For longer-term sponsorship, Deloitte also supports EB-2 and EB-3 Green Card petitions through the PERM labor certification process.
What qualifications does Deloitte expect for AI Product Manager roles?
Deloitte typically looks for a technical bachelor's degree in computer science, engineering, or data science, combined with product management experience in AI or machine learning contexts. Consulting-specific skills matter here: you'll need to demonstrate experience managing cross-functional teams, communicating technical tradeoffs to non-technical stakeholders, and delivering AI solutions in client-facing environments rather than purely internal product development.
How long does the visa sponsorship process take after receiving an offer from Deloitte?
Timeline depends on visa type and your current status. E-3 consular processing typically takes two to six weeks from LCA certification to visa stamp. H-1B transfers for candidates already in status can proceed without waiting for October 1. USCIS standard processing for new H-1B petitions runs three to six months, and premium processing, available for an additional USCIS fee, reduces that to 15 business days.
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