AI Engineer Jobs at AbbVie with Visa Sponsorship
AI Engineer jobs at AbbVie involve working across drug discovery, clinical data pipelines, and commercial analytics in a heavily regulated biotech environment. The company has an established process for sponsoring work visas across multiple categories, making it a realistic target if you need sponsorship to work in the U.S.
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Company Description
About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology, and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
As Head of Data and AI Technical Product Management, this leader serves as the global Commercial Data & AI technical product leader accountable for the operating model, portfolio strategy, investment trade-offs, product lifecycle, adoption, and product talent buildout for a large, regulated, global commercial data and AI ecosystem. The role builds and scales AbbVie’s Technical Data Product Ownership practice, serving as the IT counterpart to Commercial Business Product Owners and defining how technical data and AI products are discovered, prioritized, funded, built, launched, adopted, supported, measured, modernized, and retired. This leader translates Commercial product roadmaps and data consumer needs into durable, measurable technical product roadmaps while partnering with architecture, engineering, security, privacy, governance, analytics, and business teams. The role establishes the standards, lifecycle discipline, decision rights, adoption practices, funding mechanisms, and performance scorecards needed to move Global Commercial Data and AI from project-based delivery to product-based ownership at enterprise scale.
Responsibilities:
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Role dimensions: Serve as the global Commercial Data & AI technical product leader, owning the product operating model, multi-year portfolio strategy, investment trade-offs, lifecycle discipline, adoption strategy, and product talent buildout for a large, regulated, global commercial data and AI ecosystem. Lead the technical product roadmap across data products, AI-enabling capabilities, platform services, and self-service experiences aligned to Commercial priorities and enterprise risk expectations.
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Role scale: Own a multi-million-dollar annual Commercial Data & AI technical product portfolio supporting 30 commercial data domains, 30+ AI products and platform capabilities, 40+ brands/business units, and 120 countries. Build and scale a direct team of Technical Product Managers and product leaders, with intended responsibility for 10–20 product professionals and influence across 50–100+ matrixed engineering, AI, architecture, governance, analytics, and vendor resources as the organization matures.
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Ownership & autonomy: Own the Technical Data Product Management strategy, operating model, and product lifecycle for Commercial Data and AI capabilities, with accountability from discovery and roadmap integration through launch, adoption, support, versioning, modernization, and retirement. Partner with enterprise architecture, engineering, security, privacy, and governance leaders to make product trade-offs and ensure technical decisions align to business value, risk posture, and platform strategy.
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Decision-making: Accountable for product strategy, prioritization, roadmap trade-offs, adoption goals, lifecycle decisions, and value/risk recommendations for technical data and AI products. Define decision rights and working models with Commercial Business Product Owners and partners with architecture, engineering, security, privacy, and governance leaders on technical standards, risk acceptance, and compliance-by-design.
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Scope: Drive Global Commercial Data & AI technical product strategy across 40+ brands/business units, 120 countries, and hundreds of businesses, analytics, technology, and governance stakeholders. Partner with adjacent enterprise functions where Commercial data and AI products intersect, while maintaining clear primary accountability for the Commercial technical product ecosystem.
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Budget & investment: Own the annual engineering and technical portfolio budget and investment model; develop technical business cases, allocate funding across engineering initiatives, manage compute/cost-to-serve, and ensure vendor/partner spend aligns to product outcomes, architectural direction, and risk posture.
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Product talent buildout: Build and scale the Technical Data Product Management organization and talent bench, including hiring, coaching, performance management, succession planning, role standards, playbooks, communities of practice, and product leadership capability across direct and matrixed teams.
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Impact & influence: Serve hundreds of business, analytics, technology, and governance stakeholders globally; accountable for measurable technology outcomes such as reduced data latency, system uptime, engineering productivity gains, and compliance posture through improved data/AI reliability, discoverability, and adoption; operates at executive level, chairing or co-chairing technical steering committees and governance forums and influencing VP/SVP stakeholders through technical narratives, investment cases, operating model design, and performance metrics.
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Leadership expectations: Operate with enterprise mindset; make transparent value, risk, and capacity trade-offs; build inclusive and high-performing teams; influence senior stakeholders through clear narratives and metrics; raise product management standards across teams; and balance strategic ambition with pragmatic delivery and operational excellence.
Qualifications
Required:
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Bachelor’s Degree plus 12+ years of progressive experience in technical product management, platform leadership, data and analytics, AI-enabled products, or a related discipline, including global portfolio ownership, operating model leadership, investment accountability, people leadership, and senior accountability for measurable outcomes in a complex enterprise environment.
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Demonstrated ability to define multi-year strategy, secure alignment with executive stakeholders, and translate business objectives into funded roadmaps and measurable value realization.
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Developed, launched, operated, and improved multiple production data products and AI-enabled capabilities at enterprise scale, with demonstrated discipline across discovery, lifecycle management, reliability, adoption, governance, and value realization.
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Experience leading a shift from project-based delivery to product-based operating models in a low-maturity or evolving organization, including role definition, intake, prioritization, roadmap standards, lifecycle management, product metrics, adoption practices, and change enablement.
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Proven product talent buildout and people leadership, including building or scaling teams of Product Managers and/or product leaders, hiring, coaching, performance management, succession planning, communities of practice, and product management standards.
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Demonstrated portfolio investment ownership, including annual OPEX/CAPEX planning, funding recommendations, capacity allocation, vendor/partner spend, cost-to-serve optimization, modernization trade-offs, and linkage of investment decisions to value, adoption, reliability, and risk outcomes.
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Deep understanding of modern data ecosystems and operating models: ETL/ELT, data warehouses/lakes, APIs/event streams, metadata/lineage, access controls, and governance at scale.
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Proven leadership partnering with engineering, architecture, security/privacy, and governance to drive quality, reliability (SLAs/SLOs), compliance-by-design, and platform modernization.
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Exceptional executive communication, influence, and prioritization skills; able to lead steering forums, resolve cross-domain trade-offs, and drive adoption and change across large organizations.
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Technology fluency expected: deep fluency across modern cloud, data, analytics, AI, metadata, lineage, catalog, governance, API, eventing, orchestration, and platform reliability patterns. Experience with specific tools such as AWS, Azure, GCP, Snowflake, Iceberg, Airflow, dbt, Alation, SageMaker, Microsoft AI capabilities, Anthropic, agentic platforms, SQL, Python concepts, APIs, and AI/BI tools is illustrative and helpful, but transferable technical product leadership across comparable ecosystems is most important.
Preferred:
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Experience in regulated industries, with life sciences/pharma Commercial data and analytics preferred, including sales, marketing, market access, omnichannel, CRM, and associated regulatory/privacy considerations.
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Experience building enterprise data/AI platforms and governance operating models (data catalog, data mesh/fabric concepts, stewardship, policy enforcement) across multiple business units and geographies.
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Experience managing complex vendor ecosystems and strategic partners (RFPs, contracting, SLAs, performance management), including multi-year platform programs and large-scale change management.
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
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The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
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We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
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This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
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Get Access To All JobsTips for Finding AI Engineer Jobs at AbbVie
Frame Your Portfolio Around Life Sciences AI
AbbVie evaluates AI Engineers on domain relevance, not just technical depth. Projects involving biological datasets, clinical trial modeling, or regulatory-grade data pipelines will carry more weight than general software or consumer AI work.
Confirm Specialty Occupation Fit Before Applying
H-1B approval for AI Engineer roles hinges on demonstrating that the position requires a specific bachelor's degree field. Review USCIS specialty occupation criteria and make sure your degree aligns tightly with the role description before submitting applications.
Target Roles in AbbVie's R&D and Commercial Divisions
AbbVie's AI hiring spans research, oncology, immunology, and commercial analytics. Roles tied to drug development pipelines tend to have clearer specialty occupation justification, which strengthens the H-1B petition your employer files on your behalf.
Request Written Sponsorship Confirmation Before Accepting
Before signing an offer, confirm in writing which visa category AbbVie will sponsor and whether they cover premium processing. Large biotech employers sometimes restrict premium processing to certain seniority levels, which affects your start date planning.
Use Migrate Mate to Find Open AI Engineer Roles at AbbVie
Filter by visa type and role on Migrate Mate to surface active AI Engineer openings at AbbVie that are open to sponsorship. This saves time you'd otherwise spend manually screening job boards for sponsorship eligibility.
Plan Around PERM If You Want Permanent Residency
AbbVie sponsors EB-2 and EB-3 Green Cards, which require DOL PERM labor certification. PERM timelines frequently run 18 to 24 months before USCIS even sees your petition, so raise the green card conversation with HR early in your employment.
Frequently Asked Questions
Does AbbVie sponsor H-1B visas for AI Engineers?
Yes, AbbVie sponsors H-1B visas for AI Engineer roles. The company has a consistent track record of filing H-1B petitions across its technology and data functions, including positions in R&D and commercial analytics. You should confirm sponsorship eligibility during the recruiter screening call and clarify whether AbbVie covers premium processing for your specific role level.
How do I apply for AI Engineer jobs at AbbVie?
Applications go through AbbVie's careers portal at abbvie.com/careers. You can also browse open AI Engineer roles that include visa sponsorship on Migrate Mate, which filters listings by sponsorship eligibility. Tailor your resume to highlight AI applications in life sciences, such as clinical data modeling or bioinformatics pipelines, since domain alignment matters in biotech hiring.
Which visa types does AbbVie commonly sponsor for AI Engineer roles?
AbbVie sponsors H-1B, H-1B1 visa, E-3, TN visa, and F-1 OPT and CPT for AI Engineer positions, along with immigrant pathways including EB-2 and EB-3 for permanent residency. The right category depends on your nationality and immigration status. Australian citizens are eligible for the E-3 visa, which skips the H-1B lottery entirely and offers two-year renewable terms.
What qualifications does AbbVie expect for AI Engineer roles?
AbbVie typically looks for a bachelor's or master's degree in computer science, data science, engineering, or a related field. For H-1B purposes, your degree must align with the specific role, so a general business or liberal arts background is unlikely to qualify. Experience with machine learning frameworks, cloud infrastructure, and ideally life sciences data environments strengthens your candidacy significantly.
How long does the visa sponsorship process take for an AbbVie AI Engineer position?
For H-1B cap-subject cases, USCIS registration opens in March for an October 1 start date, so timing your offer around that cycle matters. Premium processing reduces USCIS adjudication to 15 business days once filed. E-3 visa and TN visas move faster and aren't lottery-dependent. PERM-based Green Card processes run 18 to 36 months from initiation to I-140 approval, depending on DOL backlog.