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 DescriptionThis entry-level AI Engineer will work under close supervision to apply developing technical knowledge in Software Engineering and Generative AI, performing analytic, testing, modeling, and development tasks on smaller projects, and independently on larger, more complex assignments. The role will help design, build, and deploy AI-enabled software solutions, including LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and model-serving APIs, to meet business requirements.
Responsibilities:
- Perform assigned technical and analytic tasks using established methods and tools, documents methods and results, and escalate novel or ambiguous issues.
- Support development of AI-enabled applications and fix straightforward defects under close supervision.
- Build and maintain components of LLM-based solutions, including API integrations, prompt and tool/function-calling workflows, and basic RAG pipelines (chunking, embeddings, vector search).
- Clean, transform, and analyze data with Python, SQL, and data libraries; build simple ETL steps and visualizations.
- Execute assigned test cases, including unit tests and basic retrieval or model evaluations, and help reproduce reported issues.
- Serve models and AI services through RESTAPIs and containers, prepare simple configuration changes, and follow deployment runbooks.
- Track experiments and model versions and support monitoring and CI/CD processes.
- Document work and escalation steps in tickets and knowledge base entries.
- Learn codebase, development workflows, and platform fundamentals through pairing and code reviews.
- Produce reliable technical outputs, follow quality and safety standards (including AI guardrails), document reproducible methods and records, and communicate progress and risks to project leads.
- Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, or relevant STEM certification.
- Problem decomposition, clear communication, reading documentation, collaborating through code review, and explaining results to non-technical people.
- Python and Software Fundamentals
- Core language: data types, control flow, functions, OOP, comprehensions, generators, decorators, exceptions, file I/O, virtual environments (venv, pip / uv)
- Data libraries: NumPy, pandas (cleaning, joins, groupby, time series)
- Visualization: Matplotlib, Seaborn, Plotly
- Code quality: type hints, unit testing (pytest), logging, PEP 8, packaging
- APIs and web: requests, REST concepts, FastAPI or Flask to serve models, async basics
- Tooling: Git/GitHub, Jupyter, VS Code, Docker basics
- Databases
- SQL (essential): SELECT, WHERE, JOINs, GROUP BY, HAVING, subqueries, CTEs, window functions, indexes, query optimization
- Relational databases: PostgreSQL, MySQL, or SQLite; schema design, normalization, primary and foreign keys, transactions
- Python connectivity: SQLAlchemy, psycopg2, pandas.read_sql
- NoSQL: MongoDB (documents), Redis (caching)
- Vector databases (AI-specific): embeddings, similarity search, and tools such as pgvector, Chroma, FAISS, Pinecone
- Data pipelines: ETL basics, data warehouses, Airflow concepts
- Modern GenAI Skills
- LLM APIs: Anthropic, OpenAI, structured outputs, tool/function calling
- RAG: chunking, embeddings, vector search, retrieval evaluation
- Frameworks: LangChain or LlamaIndex (know the basics, but understand what's underneath)
- Agents: tool use, multi-step workflows, basic evaluation, and guardrails
- MLOps and Deployment
- Model serving: FastAPI, Docker
- Experiment tracking: MLflow, Weights & Biases
- Cloud basics: AWS, Azure, or GCP
- CI/CD basics, monitoring, model versioning
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
Skills Required
- Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a relevant STEM certification
- Python programming and software engineering fundamentals, including object-oriented programming, testing, logging, packaging, and virtual environments
- NumPy and pandas for data cleaning, transformation, joins, grouping, and analysis
- Matplotlib, Seaborn, or Plotly visualization experience
- REST concepts and experience with requests, FastAPI, or Flask
- Git or GitHub, Jupyter, VS Code, and basic Docker
- SQL, including joins, aggregations, subqueries, CTEs, window functions, indexes, and query optimization
- Relational database knowledge, including schema design, normalization, keys, and transactions
- SQLAlchemy, psycopg2, or pandas.read_sql
- MongoDB and Redis
- Vector databases, embeddings, similarity search, and RAG concepts
- ETL basics, data warehouses, and Airflow concepts
- LLM APIs, including Anthropic or OpenAI, structured outputs, and tool/function calling
- RAG pipelines, including chunking, embeddings, vector search, and retrieval evaluation
- Basic LangChain or LlamaIndex knowledge
- Agents, tool use, multi-step workflows, evaluation, and guardrails
- Model serving with FastAPI and Docker
- MLflow or Weights & Biases for experiment tracking
- Basic AWS, Azure, or GCP knowledge
- CI/CD, monitoring, and model versioning fundamentals
- Clear communication, problem decomposition, documentation, collaboration through code review, and ability to explain results to nontechnical audiences
AbbVie Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AbbVie and has not been reviewed or approved by AbbVie.
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Retirement Support — Retirement programs are portrayed as a standout, with a dollar‑for‑dollar 401(k) match up to 6% and an additional annual company contribution based on age and service. Feedback suggests this materially boosts perceived total compensation for many U.S. employees.
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Parental & Family Support — Paid parental and caregiver leave are emphasized, including up to 12 weeks of fully paid parental leave for all parents and 4 weeks of paid caregiver leave in the U.S. Feedback suggests these policies are a meaningful differentiator for employees balancing family needs.
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Leave & Time Off Breadth — Time off is described as extensive, with tiered vacation that scales with tenure, 17 company holidays, and two paid volunteer days in the U.S. Feedback suggests the breadth of leave contributes notably to overall benefits satisfaction.
AbbVie Insights
What We Do
AbbVie is a global biopharmaceutical company focused on creating medicines and solutions that put impact first — for patients, communities, and our world. We aim to address complex health issues and enhance people's lives through our core therapeutic areas: immunology, oncology, neuroscience, eye care, aesthetics and other areas of unmet need.
