Applied AI Engineer Jobs in Illinois
Applied AI Engineer jobs in Illinois are open across Chicago, Will County, and North Chicago and other Illinois metros, with employers like JPMorganChase, Amazon Web Services (AWS), and SentiLink hiring at every experience level. Find a role that fits below and apply directly.
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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
Join an inclusive, collaborative Business Technology Solutions (BTS) team as a Sr Engineer, Applied AI & Engineering Platforms at AbbVie. This is a hands-on, lead technical engineering role at the center of AbbVie’s generative and agentic AI transformation — building intelligent, autonomous systems and scalable agentic workflows that will accelerate drug discovery, streamline clinical and regulatory operations, and reimagine how AbbVie works across every function.
You will design and own the AI foundations layer that underpins all agentic capabilities across the enterprise, establish engineering standards that make AI systems reliable and auditable in GxP-regulated environments, and serve as a technical authority guiding platform teams, data scientists, and application engineers across the organization.
This is not a research or prototyping role. You will architect, build, and operate production-grade multi-agent systems used in clinical, commercial, and operational domains — working alongside enterprise architecture, platform security, data engineering, MLOps, and domain subject matter experts to ensure every system is deployable, governed, and compliant from day one.
Responsibilities:
Agentic System Design & Engineering
- Architect and own production-grade multi-agent systems using orchestration frameworks (LangChain, LangGraph, CrewAI, OpenAI Agents SDK, AutoGen/AG2, Semantic Kernel), making deliberate decisions on state management, routing, memory architecture, and failure handling.
- Design agent cognitive architectures — planning loops (ReAct, Reflexion, CoT), tool-use patterns, memory systems (short-term, episodic, semantic), and self-evaluation loops.
- Build multi-agent coordination patterns (supervisor–worker, peer collaboration, A2A protocols) aligned with emerging open standards including MCP server integration to connect agents to enterprise systems, clinical data platforms, and regulatory repositories.
AI Foundations Layer
- Design and maintain shared AI infrastructure: LLM gateway/routing, embedding services, vector stores, RAG pipelines, prompt management, and model evaluation harnesses across all agentic products.
- Establish model selection and governance spanning hosted providers (Claude, GPT, Gemini) and self-hosted models, including fine-tuning pipelines (LoRA/QLoRA) for pharmaceutical-specific tasks.
- Build context engineering standards — managing context windows, retrieval strategies, chunking, re-ranking, hybrid search, and query routing for enterprise-scale clinical and scientific knowledge — with guardrails, safety layers, content filters, and HITL escalation appropriate for GxP environments.
Agentic Engineering SDLC
- Define the end-to-end SDLC for agentic systems — from design through evaluation, deployment, and continuous monitoring — treating agent behavior as a first-class software artifact subject to change control.
- Build agent evaluation frameworks (golden test sets, LLM-as-judge scoring, regression detection, task-completion benchmarks, latency/cost dashboards) and CI/CD pipelines with automated evaluation gates, drift detection, and rollback capabilities.
- Establish traceability, audit logging, and versioning standards supporting GxP validation, 21 CFR Part 11, and AbbVie’s AI governance policy.
Observability, Reliability & AIOps
- Implement full-stack observability (LangSmith, Langfuse, OpenTelemetry): trace-level logging, token/cost tracking, latency profiling, and anomaly detection on agent behavior.
- Own production reliability — retry logic, fallback strategies, circuit breakers, graceful degradation, and HITL escalation for regulated workflows. Monitor for behavior drift and decision inconsistency; implement continuous feedback loops without introducing regressions.
- Integrate agentic services with enterprise platforms (Salesforce, MuleSoft, Veeva, SAP, Databricks, ServiceNow) using MCP and standardized API patterns.
Governance, Compliance & Responsible AI
- Design agent authorization models operationalizing AbbVie’s AI risk tiers (HIGH/LOW), defining what agents can access, act on, and decide autonomously versus what requires human approval.
- Implement governance controls aligned with FDA AI/ML guidance, ICH E6/E8, EU AI Act, and AbbVie internal policy — ensuring compliance with data residency, privacy (HIPAA, GDPR), least-privilege access, prompt injection defense, and secure MCP/A2A integrations.
- Build validation artifacts satisfying audit requirements for agents in clinical, regulatory, and GxP-controlled workflows.
Cross-Functional Technical Leadership
- Partner with product managers, data scientists, enterprise architects, platform security, and domain teams to translate pharmaceutical problems into agent system designs; define reusable patterns and shared platform components that accelerate development across teams.
- Mentor engineers on the agentic AI platform, conduct architecture reviews, establish engineering standards, and foster a culture of production-quality AI development while driving adoption of emerging standards (MCP, A2A, evaluation benchmarks) relevant to AbbVie’s environment.
Qualifications
Required:
- Minimum years of experience: 6+ with Bachelors, or 5+ with Masters, or 0+ with PhD in software engineering with demonstrated depth in AI/ML systems, NLP/LLM applications, or production AI platforms — including experience building Generative AI or LLM-powered applications in production environments.
- Demonstrated hands-on experience architecting and deploying production-grade AI agent or multi-agent systems — not prototypes or POCs — using at least one major orchestration framework (LangChain, LangGraph, CrewAI, OpenAI Agents SDK, AutoGen/AG2, or Microsoft Semantic Kernel).
- Strong Python proficiency including async programming (asyncio), RESTful API design (FastAPI), system design patterns for scalable distributed AI systems, and production-quality coding practices.
- Hands-on experience building and operating RAG pipelines: embedding models, vector databases (e.g., pgvector, Pinecone, Azure AI Search), chunking strategies, hybrid retrieval, and retrieval evaluation. Familiarity with LlamaIndex or similar RAG frameworks is a plus.
- Experience with one or more cloud AI platforms (AWS Bedrock, Azure AI Foundry, or Google Vertex AI) including serverless inference and managed agent services.
- Solid understanding of prompt engineering at the system level: system prompt design, structured output formats, tool-call schemas, context engineering, and prompt versioning.
- Clear communication skills — ability to articulate agent architecture decisions, risk tradeoffs, and compliance implications to both technical engineers and non-technical business stakeholders.
Preferred:
- Working proficiency with LLMOps/AIOps tooling (LangSmith, Langfuse, MLflow, or equivalent) for agent observability, experiment tracking, and production monitoring.
- Experience designing and implementing agent evaluation frameworks including test dataset design, LLM-as-judge scoring, regression benchmarking, and responsible AI practices.
- Open-source contributions, published work, or conference presentations in agentic AI, multi-agent systems, LLM engineering, machine learning, or related areas.
- Strong experience with MCP (Model Context Protocol), A2A (Agent-to-Agent), or equivalent tool-integration and agent communication standards; TypeScript or Go proficiency for MCP server development or full-stack AI delivery.
- Experience in pharmaceutical, life sciences, biotech, or other regulated industry environments with exposure to GxP, 21 CFR Part 11, FDA AI/ML guidance, ICH E6/E8, or ISO 42001 standards.
- Hands-on experience integrating AI agents with enterprise platforms (Salesforce, Veeva Vault, SAP, ServiceNow, Databricks, MuleSoft) or processing multimodal clinical/scientific data.
- Background in distributed systems or microservices architecture (event-driven, serverless, Kubernetes); familiarity with Docker, container orchestration, PyTorch, or Hugging Face for model experimentation.
- AWS, Azure, or GCP professional-level certifications; familiarity with AI-assisted development workflows (Cursor AI, GitHub Copilot).
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- 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.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our short-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
See All 13 Applied AI Engineer Jobs in Illinois
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Find Applied AI Engineer JobsApplied AI Engineer Jobs by City in Illinois
Where Illinois roles are concentrated, by current openings.
Applied AI Engineer Job Market in Illinois
A snapshot from current Illinois openings, updated as new roles post.
Who's Hiring
- JPMorganChase3

- Amazon Web Services (AWS)2

- SentiLink2

- AbbVie1

- Amazon1

Top Industries Hiring
- Technology & Software5
- E-Commerce & Online Marketplaces2
- Retail2
- Banking & Financial Services1
- Biotechnology & Pharmaceuticals1
What Illinois Employers Look For
The qualifications that appear most often in applied AI engineer jobs across Illinois.
- Proficiency in Python with hands-on experience building and deploying machine learning models
- Experience with large language models and frameworks such as PyTorch, Hugging Face, or LangChain
- Familiarity with MLOps tooling including model versioning, monitoring, and CI/CD pipelines
- Bachelor's or master's degree in computer science, machine learning, or a closely related field
- Experience integrating AI models into production software systems via APIs or microservices
- Working knowledge of cloud platforms such as AWS, Google Cloud, or Azure for model serving
Applied AI Engineer Jobs in Illinois: Frequently Asked Questions
How many applied AI engineer jobs are there in Illinois?
There are 13+ applied AI engineer openings in Illinois on Migrate Mate as of June 2026, with the most roles in Chicago, Will County, and North Chicago. New positions post regularly as employers across Illinois hire.
How much do applied AI engineers make in Illinois?
Applied AI engineers in Illinois earn a median of about $132,110 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $80,980 for the lowest 10% to over $194,740 for the top 10%. Pay rises with experience, specialty, and employer.
Which Illinois cities have the most applied AI engineer jobs?
Chicago, Will County, and North Chicago have the most applied AI engineer openings in Illinois right now, with additional roles spread across smaller metros statewide.
Which companies hire applied AI engineers in Illinois?
Employers hiring applied AI engineers in Illinois include JPMorganChase, Amazon Web Services (AWS), and SentiLink, based on current listings on Migrate Mate as of June 2026.
Are there remote applied AI engineer jobs in Illinois?
Yes. About 38% of applied AI engineer openings tied to Illinois are remote or hybrid as of June 2026. The rest are on-site roles based in Illinois metros.
How do I apply for applied AI engineer jobs in Illinois?
You can apply to applied AI engineer jobs in Illinois directly on Migrate Mate. Search the listings above, find roles that match your experience and preferred Illinois location, then apply to each one that fits.
See All 13 Applied AI Engineer Jobs in Illinois
Find roles in Illinois that match your experience and apply in just a few clicks.
Find Applied AI Engineer Jobs