AbbVie

Job Description Job Description 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 . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description While the AI innovation race in Biopharma is focused on Drug discovery, Product Development/ CMC represents the next barrier/ bottleneck. The complexity of biological systems, the rigor of regulatory expectations, the pace of pipeline growth, and the enormous value at stake make this one of the highest-leverage domains for applied data science and AI in the entire pharmaceutical value chain. We here at BTS - PDST, are building a dedicated, AI-native team that is driving cutting edge programs across early stage, late stage and commercial product development to accelerate E2E product development and launch, maximize yields of block buster products. Through our deep collaboration with PDST scientists we are boldly reimagining how Abbvie can bring our pipeline products and lifesaving drugs to patients faster, safer and in cost effective manner fueled by AI. Principal Data Engineer is a highly technical, AI-native role responsible for designing, building, and operating production-grade data pipelines and data products that power AI/ML, analytics, and automation across AbbVie's CMC and manufacturing ecosystem. This role is embedded inside PDST and works at the frontier of pharmaceutical data engineering. You will integrate and harmonize data from the full spectrum of manufacturing and development systems - including MES, historians, LIMS, QMS, ERP, and instrument platforms - and transform it into reliable, governed, semantically rich data assets that data scientists, process engineers, and AI systems can actually use. Enterprise-scale scope: Enterprise-scale biologics portfolio spanning clinical, commercial, and lifecycle stages Building AI playbook for the future: First-in-AbbVie and first-in-biologics analytical approaches; you build the AI playbook for the future Growth and Impact: Direct impact on regulatory submissions, commercial readiness, and manufacturing decisions through deep cross-functional exposure to manufacturing, quality, regulatory, and scientific leadership Mission: Every model you build helps ensure safe, reliable medicines reach patients at scale Responsibilities Data Ingestion & Integration Design and implement scalable, robust data ingestion pipelines that connect CMC and manufacturing source systems - including MES (Manufacturing Execution Systems), process historians, LIMS, QMS, ERP platforms, and instrument data sources - to centralized and federated data environments. Build connectors, adapters, and integration layers that handle the heterogeneous data formats, protocols, and latency profiles characteristic of pharmaceutical manufacturing environments. Support both batch and real-time/streaming data patterns, selecting appropriate architectures based on use case requirements. Data Harmonization & Semantic Modeling Develop and maintain harmonized data models and ontologies that bring consistency to CMC and manufacturing data across sites, systems, and modalities. Execute semantic mapping efforts that align source system fields, units, and identifiers to enterprise data standards and scientific meaning. Collaborate with process scientists, analytical chemists, and manufacturing engineers to ensure data models accurately reflect domain reality. Data Quality, Observability & Governance Implement automated data quality controls, validation frameworks, and anomaly detection mechanisms across pipeline layers. Build and maintain data lineage documentation and metadata infrastructure, enabling full traceability from source system to AI model input. Establish pipeline observability practices - monitoring, alerting, SLA tracking - to ensure data product reliability in production. Support data governance practices aligned with GxP requirements, 21 CFR Part 11, and AbbVie data standards. AI/ML Enablement & Data Product Development Architect and deliver governed, versioned, reusable data products purpose-built for AI/ML consumption, including feature stores, curated datasets, and vector-ready data layers for RAG and LLM applications. Partner closely with data scientists, ML engineers, and process modelers to understand model data requirements and translate them into reliable, scalable data infrastructure. Accelerate AI program delivery by eliminating data bottlenecks - not by workarounds, but by solving root causes structurally. Platform & Operational Enablement Contribute to the design and evolution of PDST's cloud-based data platform, including lakehouse architecture, data cataloging, access control, and compute infrastructure. Write and maintain infrastructure-as-code, CI/CD pipelines, and automated testing frameworks for data systems. Support platform onboarding of new CMC data domains and manufacturing sites, ensuring consistent application of standards and patterns. Provide operational support for production data pipelines, maintaining uptime and data freshness commitments. Stakeholder Engagement & Scientific Leadership Influence technical decision-making without formal authority - earning trust through scientific rigor, transparent methodology, and demonstrated business impact. Qualifications Required: Bachelor's Degree Computer Science, Data Engineering, Information Systems, Software Engineering, Bioinformatics, or a closely related technical field plus 6 years' experience; Master's Degree plus 5 years' experience; PhD plus 0 years' experience. Respective years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Expert-level proficiency in Python for data engineering tasks - pipeline development, transformation logic, data validation, and automation. Strong SQL skills across modern analytical and transactional databases; comfort with both ANSI SQL and platform-specific dialects. Demonstrated experience with cloud data platforms (AWS, Azure, or GCP) and modern data stack components - including tools such as dbt, Spark, Airflow, Databricks, Snowflake, or equivalents. Develop ETL/ELT pipelines using tools such as Informatica, Talend, Apache NiFi, and cloud-native services (e.g., AWS Glue, Azure Data Factory). Implement master data management (MDM), metadata management, and data cataloging solutions to ensure proper data lineage, accessibility, and compliance. Set and enforce standards for API development and data integration (REST, GraphQL, OData), enabling seamless integration using microservices architectures. Ownership orientation: you define your own problem space, drive solutions to completion, and hold yourself accountable to outcomes - not just outputs. Solution-architect instinct: you think before you build, consider the full landscape of available approaches, and choose tools based on fit-for-purpose reasoning rather than familiarity or trend. Scientific integrity: you build models you can explain, defend, and improve - and you apply the same standard to the work of others. Influence through credibility: you earn the confidence of scientists, engineers, and quality professionals by being right, being clear, and being useful - not by title or volume. Bias for impact: you are drawn to problems where the stakes are high and the analytical opportunity is real, and you are energized rather than intimidated by ambiguity. Preferred: 3+ years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Familiarity with technology transfer workflows, process characterization study design, or commercial process validation (PPQ/PV) in a biologics or pharmaceutical context. Experience in pharmaceutical, biotech, or other regulated life sciences manufacturing environments. Familiarity with GxP data principles, 21 CFR Part 11 compliance, or data integrity requirements in regulated industries. Prior exposure to manufacturing source systems such as MES, process historians (e.g., OSIsoft PI/AVEVA), LIMS, QMS, or ERP platforms Experience building data infrastructure for AI/ML programs - including feature engineering pipelines, model training datasets, or vector/embedding data layers for RAG architectures. Knowledge of biologics manufacturing processes (e.g., upstream cell culture, downstream purification, fill-finish) or CMC development workflows. Familiarity with data mesh, data fabric, or federated data architecture patterns. Experience with graph databases, knowledge graphs, or ontology frameworks applied to scientific or manufacturing data. Contributions to open-source data tooling or demonstrated engagement with the modern data engineering community. Design logical, physical, and conceptual data models using modeling tools (e.g., Erwin, PowerDesigner, dbt). . click apply for full job details

Job Description Job Description 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 . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description As a discipline expert and technology leader, the Principal AI Engineer II will define and advance the strategy, architecture, and engineering practices required to develop, deploy, and scale artificial intelligence solutions across AbbVie. This role will investigate, identify, and implement state-of-the-art technology platforms that drive productivity and efficiency gains in own function and throughout multiple business areas. Technical leader acting at a group, department, and cross-functional levels. Responsible for managing the Data, Solutions, Business, and/or technology environments and tying them to the Enterprise Architecture and other architectures designs. Responsibilities: Define and advance AI engineering strategy, architecture, standards, and roadmaps aligned with AbbVie's business and technology objectives. Architect and build secure, scalable, reusable AI platforms, services, developer tools, and components that support enterprise adoption. Lead production-grade AI solutions from ideation and prototyping through development, testing, validation, deployment, monitoring, continuous improvement, and retirement. Integrate AI platforms with AWS services and enterprise data, software, security, identity, and infrastructure environments. Establish practices for evaluation, testing, versioning, release management, observability, performance monitoring, incident response, and operational support. Apply risk-based approaches to compliance, GxP, data integrity, privacy, cybersecurity, documentation, traceability, human oversight, and responsible AI. Partner with Quality, Regulatory, Legal, Privacy, Information Security, scientific, technical, and business stakeholders to deliver fit-for-purpose solutions. Serve as a trusted technical advisor, facilitate alignment, influence decisions without direct authority, and communicate complex tradeoffs and recommendations to technical and non-technical audiences. Evaluate emerging technologies, lead innovation and proof-of-concept efforts, and guide promising solutions into sustainable production capabilities. Mentor engineers, advance engineering maturity, promote knowledge sharing, and represent AbbVie in relevant technical communities and partner engagements. Qualifications Required Bachelor's degree with 9 years' experience, Master's degree with 8 years' experience, or PhD with 4 years' in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline. Demonstrated experience designing, deploying, and operating production-scale AI and machine learning systems. Strong experience in AI/platform engineering, including scalable platforms, reusable components, and production-grade AI solutions. Demonstrated experience designing, building, deploying, and supporting solutions using AWS systems and services. Strong software and cloud engineering practices, including secure design, automated testing, CI/CD, containerization, monitoring, and operational support. Experience working in a regulated environment, preferably pharmaceutical, biotechnology, healthcare, medical device, or life sciences. Experience supporting the full solution lifecycle, including feasibility, design, development, testing, validation, deployment, and ongoing operations. Strong understanding of risk management, validation, change control, data integrity, cybersecurity, privacy, documentation, and quality requirements. Demonstrated ability to manage complex stakeholders, influence technical and business decisions, and collaborate across organizational boundaries. Excellent communication skills with senior leaders, technical teams, scientific experts, business partners, and external collaborators. Demonstrated innovation and mentoring experience, including advancing engineering practices and delivering measurable impact. Preferred Experience with enterprise AI governance, responsible AI, model validation, human oversight, and AI lifecycle management. Experience with MLOps and production engineering, including model evaluation, APIs, microservices, CI/CD, observability, and infrastructure as code. Open-source contributions or technical thought leadership through publications, patents, or industry working groups. Experience leading cross-functional product development from feasibility through validation and production implementation. Enterprise AI or platform experience, including AWS architecture, governance, security, and integration with enterprise environments. 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 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 -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html

Job Description Job Description 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 . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description We are building a team that develops AI agents to solve hard security problems and you will be tackling the hardest ones. This is a hands-on, senior IC role. You will architect, build, and ship agentic AI systems that operate autonomously within security environments, while also driving the technical direction and standards for how these systems are built, tested, and secured. This is not a management role and not a pure research role. You will write code, ship systems, and get your hands dirty but you will be working on problems where there is no playbook yet. You will define the approach, build the proof of concept, harden it for production, and write the technical guidance others follow. Responsibilities: Architect and build AI agent systems for security operations autonomous detection, investigation, response, threat hunting, vulnerability analysis, and risk assessment Tackle the novel, high-complexity problems: adversarial robustness of agent systems, secure agent-to-agent communication, guardrails for autonomous decision-making in high-stakes security contexts Develop frameworks, tooling, and patterns for building secure and reliable agentic AI systems then use them yourself Conduct original research and experimentation on agentic AI applied to offensive and defensive security, translating findings into working code Build proof-of-concept exploits and adversarial tests against agentic AI systems to identify failure modes and inform defensive design Develop and publish technical guidance and policy for agentic AI security grounded in systems you have built and broken Independently author security position papers on emerging technologies strategic, high-level documents that frame organizational thinking on new threat domains and drive downstream policy and technical guidance Serve as a subject matter expert and key driver of the AI Cybersecurity Maturity program, spanning application security, training, AI controls and infrastructure, AI discovery and inventory, operations and incident response, and policy and procedure development Integrate LLMs, custom models, and security tooling (SIEM, EDR, SOAR, cloud platforms, vulnerability scanners) into agent architectures Evaluate and adopt emerging AI capabilities (new models, frameworks, techniques) and determine their applicability to security problems Set technical direction for agent development practices, including evaluation frameworks, testing methodologies, and deployment patterns Mentor and elevate other engineers on the team through code review, design guidance, and technical leadership Qualifications Required: Bachelor's Degree with 9 years' experience; Master's Degree with 8 years' experience; PhD with 4 years' experience. Respective years of experience in cybersecurity, security engineering, or security research with substantial hands-on technical depth Strong software engineering skills you ship production systems, not just prototypes. Python required; additional languages a plus Deep expertise in at least two of: security operations, application security, threat intelligence, vulnerability research, detection engineering, offensive security, cloud security Demonstrated experience building AI agents and AI/ML-powered security tools or automation that operated at scale Hands-on experience with agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot, Aider, or similar) as part of your daily development workflow you build with agents, not just build agents Track record of original technical work published research, open-source tooling, conference presentations, or equivalent evidence of independent technical contribution Ability to work at the intersection of security and AI: you understand both the security implications of AI systems and how to apply AI to security problems Experience developing technical standards, frameworks, or guidance that others adopted Strong written and verbal communication you can explain complex technical concepts to both engineers and senior leadership, and you can write strategically about emerging technology risks at a level that shapes organizational direction Preferred: Experience with agent orchestration and autonomous systems (custom frameworks, LangChain, AutoGen, MCP, or similar) Background in adversarial ML, AI red teaming, or AI safety Familiarity with security compliance frameworks (NIST, ISO 27001, SOX) and how they apply to AI systems Published work (Black Hat, DEF CON, OWASP, academic journals, or equivalent venues) Experience in regulated industries (financial services, healthcare, critical infrastructure, government/defense) Contributions to open-source security projects OWASP, MITRE ATT&CK, or similar framework expertise applied in production environments Security clearance eligibility (not required) 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 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 -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html