Jobs / United States / Abbvie US LLC

Abbvie US LLC

Engineer, Technology I

Mettawa, IL, US Posted today

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 177 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Abbvie US LLC paid sponsored hires in similar roles1 certified filing for “PRINCIPAL ENGINEER, TECHNOLOGY” (Computer Network Architects) in IL: $178k–$178k, median $178k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 177 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Abbvie US LLC paid sponsored hires in similar roles
1 certified filing for “PRINCIPAL ENGINEER, TECHNOLOGY” (Computer Network Architects) in IL: $178k–$178k, median $178k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

AbbVie’s Business Technology Solutions (BTS) Information Research (IR) organization is seeking an Engineer, Technology I to help deliver trusted, well-structured, AI-ready data products within ARCH, AbbVie’s R&D Convergence Hub. As part of the DELOS team — Data Exploration and Linked Outcome Solutions — this role helps build the reliable data foundations needed to advance analytics, reporting, knowledge graph capabilities, machine learning, and AI-enabled use cases across R&D. In this role, you will independently design and develop data pipelines and curated data assets within assigned projects, applying established architecture, engineering patterns, and governance standards. You will collect, integrate, normalize, model, and document research data; implement quality checks; and support publication to the ARCH knowledge graph. Rather than developing AI models directly, you will prepare reliable, accessible, and appropriately governed data for analytics, data science, and AI-enabled use cases. Working with R&D stakeholders, data scientists, machine learning engineers, platform teams, architects, and data owners, you will translate defined scientific and business requirements into dependable data solutions. You will perform routine and complex engineering tasks independently, understand project objectives and your contribution to them, adapt your approach when needed, and communicate progress, risks, and issues. You will collaborate with internal and contracted engineers on assigned work, seeking guidance on broader architecture decisions and escalating issues outside your scope. Under the direction of the Associate Director – Data Strategy, AI & Knowledge Enablement, this role contributes to AbbVie’s R&D data transformation by delivering consistent, well-documented data solutions within agreed project scope and timelines. You will learn and apply new methods and technologies to help research partners use trusted data for scientific decision-making. **This is a hybrid role based in Lake County, IL (Tue, Wed, Thu) Responsibilities • Data Pipeline & Product Development: Independently design and develop pipelines and curated data assets for assigned scientific or business use cases. Collect, integrate, normalize, model, and transform data from databases, applications, APIs, licensed external sources, and other systems using established engineering patterns. • Reliable Project Delivery: Perform routine and complex engineering tasks competently and independently, producing reliable and consistent results within agreed timelines. Understand broader project objectives, organize assigned work, and adapt your approach when requirements or priorities change. • AI & Knowledge Graph Data Preparation: Clean, standardize, enrich, and structure data and documents for downstream analytics, machine learning, retrieval-augmented generation (RAG), and knowledge discovery. Organize metadata, support established chunking and embedding workflows, and prepare curated assets for publication to the ARCH knowledge graph. • Data Quality & Technical Documentation: Implement defined data quality checks and maintain technical documentation for pipelines and data assets, including metadata, lineage, transformations, assumptions, and usage guidance. Apply established access, privacy, licensing, and governance requirements. • Collaboration & Progress Communication: Work with scientific, business, engineering, and platform partners to clarify requirements and deliver assigned work. Clearly present project objectives, progress, risks, and issues; collaborate with internal and contracted contributors without responsibility for directing their delivery. • Operations & Method Improvement: Monitor assigned pipelines for performance, freshness, failures, and resour

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