Level

AstraZeneca

Digital Eng, Robotics & Automation, Process Sciences, Analytics and Technology, CGT

AstraZeneca is hiring a Digital Eng, Robotics & Automation, Process Sciences, Analytics and Technology, CGT. It pays $90k-$135k a year and Level rates it ; you can apply on Level.

AI in this role

computer-vision

We are seeking a Engineer, Digital and Data Science – Robotics and Automation within Process Sciences, Analytics and Technology, Cell and Gene Therapy. This engineer role will execute software, data, systems-integration, and digital-connectivity work required to develop and operate advanced robotic and automation platforms supporting AZD0120 and future cell and gene therapy programs.


This engineer will build and support reliable interfaces, reusable software components, data pipelines, workflow logic, monitoring tools, and technical documentation that connect robotics with laboratory, manufacturing, and enterprise systems. The role will support platform scaling and the transition of robotic and digitally enabled workflows from laboratory development through manufacturing implementation and deployment for future commercial production. The engineer will contribute to reusable digital, data, and automation architectures that improve standardization, reliability, maintainability, technology transfer, lifecycle support, and expansion across cell therapy programs.


The successful candidate will work hands-on in laboratory and engineering environments with automation engineers, scientists, Manufacturing Science and Technology, QC, Manufacturing Operations, Quality, Digital, IT, Informatics, and external technology partners. The engineer will directly support laboratory testing, engineering runs, workflow execution, equipment operation, troubleshooting, and data review in addition to software and data responsibilities. A central expectation is disciplined collaboration with Digital and IT so that locally useful solutions are also secure, supportable, governed, interoperable, and aligned with enterprise architecture and data standards.

This position reports to the Executive Director, Automation, Robotics & Technical Writing and is based in Tarzana, California.


Accountabilities

Software Engineering for Robotics and Automation

·     Develop, configure, test, deploy, and maintain software components, scripts, utilities, services, and interfaces supporting robotic and modular automation workflows.

·     Implement equipment and instrument connectivity using approved APIs, software development kits, middleware, message-based integration, database interfaces, equipment drivers, serial communication, or industrial protocols, as applicable.

·     Contribute to workflow orchestration, scheduling logic, device-state management, handshakes, alarms, exception handling, pause-and-resume behavior, and recovery pathways.

·     Apply maintainable software-engineering practices using Digital- and IT-approved technology stacks, development environments, repositories, source-control and peer-review practices, automated testing, CI/CD approaches, release documentation, configuration management, and controlled deployment.

·   Develop within approved enterprise technology stacks and integration patterns, which may include Git-based repositories, Azure DevOps or comparable lifecycle tooling, APIs, containerized applications, cloud services, automated test frameworks, observability tooling, and software release-management capabilities, as appropriate to the intended use and support model.

·     Troubleshoot software defects, interface failures, timing issues, data mismatches, device-state conflicts, and workflow interruptions using logs, diagnostics, test evidence, and structured root-cause analysis.

·     Create reusable integration patterns and libraries that reduce one-off customization and improve scalability across automation platforms.


Data Engineering, Contextualization and Traceability

·     Design and maintain data pipelines that capture, validate, transform, contextualize, store, and expose robotics- and equipment-generated data for authorized scientific, engineering, and operational use.

·     Define and implement data structures for process parameters, equipment states, alarms, workflow events, sample and material identity, metadata, user actions, timestamps, and execution history.

·     Support end-to-end sample and material lineage, data provenance, auditability, and traceability across connected workflows and systems.

·     Build dashboards, automated reports, alerts, and engineering views that provide visibility into workflow status, failures, cycle time, utilization, interventions, and system performance without replacing accountable business or quality records.

·     Perform data-quality checks and support reconciliation of missing, duplicated, delayed, incorrectly mapped, or out-of-range data.

·     Partner with data platform owners to align interfaces, metadata, retention, access, and data-product practices with enterprise standards.


Digital and IT Partnership, Architecture and Cybersecurity

·     Work with Digital, IT, Informatics, system owners, and enterprise architects to translate scientific and automation needs into secure, supportable software and data solutions.

·   Bridge Operational Technology (OT), Laboratory Technology (LT), and Information Technology (IT) environments to enable secure, interoperable, and scalable automation ecosystems spanning laboratory, manufacturing, and enterprise systems.

·     Contribute to interface contracts, data-flow diagrams, network and hosting requirements, identity and access models, environment strategies, backup and recovery expectations, monitoring, and support handoffs.

·   Collaborate with Manufacturing, Quality, Digital, and IT to integrate robotics and automation platforms with manufacturing execution systems (MES), electronic batch records, LIMS, process historians, manufacturing analytics platforms, and related systems supporting cGMP operations.

·     Use approved development environments, repositories, cloud services, integration patterns, and deployment processes; avoid unsupported shadow systems and unmanaged production dependencies.

·     Support cybersecurity reviews, threat and vulnerability remediation, least-privilege access, secrets management, patching coordination, logging, incident support, and lifecycle planning for connected automation assets.

·     Clearly define ownership boundaries among PSAT, vendors, Digital, IT, Quality, and business system owners, including escalation pathways and operational support responsibilities.


AI-Enabled Robotics and Advanced Analytics

·     Collaborate with Digital, IT, Data Science, Quality, and scientific SMEs to evaluate AI/ML use cases for robotics monitoring, anomaly detection, predictive maintenance, computer vision, scheduling, workflow optimization, and operator decision support.

·   Support development and application of digital twins, simulation environments, virtual commissioning models, workflow emulation, and robotics or process models that improve design evaluation, capacity planning, troubleshooting, optimization, deployment readiness, and lifecycle improvement.

·   Evaluate and support computer-vision capabilities for robotic guidance, barcode and label verification, object and container identification, material tracking, automated inspection, anomaly detection, and workflow monitoring, subject to defined intended use, testing, and human oversight.

·     Prepare trusted, contextualized, and appropriately governed data suitable for model development, evaluation, and monitoring.

·     Prototype AI-enabled capabilities only within approved environments and with defined intended use, acceptance criteria, human oversight, source traceability, access controls, and lifecycle ownership.

·     Evaluate model and workflow performance using documented test data; identify limitations, false positives, drift, unsupported outputs, and operational risks before broader deployment.

·     Ensure AI outputs remain advisory unless specifically approved for another intended use, and ensure qualified personnel retain accountability for scientific, operational, quality, and regulatory decisions.

·     Contribute to reusable AI integration patterns, model interfaces, monitoring approaches, and documentation that enable responsible scale-up across robotics platforms.


Robotics Platform and Process-Workflow Enablement

·     Configure and support software and data integration for platforms such as Multiply Labs integrated robotic manufacturing systems, HighRes Biosolutions, Hamilton, and comparable robotic or modular automation systems.

·   Support development and scaling of advanced robotic cell therapy manufacturing architectures, including modular automation, integrated robotic process cells, orchestration across unit operations, and future-state robotic cell therapy factory concepts using platforms such as Multiply Labs and comparable technologies.

·     Partner with scientists and automation engineers to map current and future workflows and convert process requirements into software behavior, interface requirements, data requirements, and testable acceptance criteria.

·     Support connected workflows involving cell processing, liquid handling, incubation, centrifugation, sampling, analytical testing, barcode identification, imaging, material movement, and related operations.

·     Participate in prototyping, workflow simulations, engineering runs, feasibility studies, equipment testing, commissioning, and operational-readiness activities.

·   Support the transition from prototype and laboratory automation to manufacturing-ready solutions by strengthening robustness, repeatability, reliability, maintainability, cybersecurity, data integrity, supportability, capacity, and operational readiness.

·     Develop practical tools and user interfaces that improve usability while preserving approved process intent, data integrity, and appropriate operator controls.

·   Contribute to deployment planning, technology transfer, site implementation, commissioning, qualification, support-model definition, and lifecycle management for automation intended to support future clinical and commercial production.


Hands-On Laboratory Testing and Workflow Execution

·     Perform hands-on work in laboratory and engineering environments to support development, integration, and testing of robotic and automation workflows.

·     Execute laboratory studies and engineering runs using automated and manual methods to assess workflow feasibility, software behavior, equipment integration, sample handling, data capture, and operational usability.

·     Operate and support laboratory and automation equipment used for cell processing, liquid handling, centrifugation, incubation, sampling, analytical testing, barcode identification, imaging, and material movement, following applicable procedures and training requirements.

·     Prepare equipment, instruments, consumables, samples, reagents, and test materials for automation development, integration testing, FAT/SAT support, commissioning, qualification, and workflow demonstrations.

·     Collect and review experimental, equipment, software, and workflow data; compare observed results with defined requirements and acceptance criteria; and document anomalies, limitations, and recommended improvements.

·     Partner with scientists and automation engineers to evaluate manual-to-automated workflow translation, including sequence accuracy, timing, mixing, transfers, holds, recovery steps, operator interventions, and sample or material traceability.

·     Support controlled studies that challenge expected operating ranges, alarms, exception handling, pause-and-resume functions, recovery pathways, data transfer, and equipment or interface failure modes.

·     Use direct laboratory observations, run data, system logs, and test evidence to troubleshoot issues and distinguish process, equipment, software, interface, consumable, and user-workflow contributors.

·     Maintain accurate laboratory records, electronic data, test evidence, equipment-use records, deviations, and technical observations in accordance with applicable data-integrity, safety, quality, and documentation requirements.

·     Support laboratory readiness, safe work practices, equipment care, housekeeping, inventory coordination, and transfer of validated or qualified workflows to operational users.


Testing, Validation and Computerized-System Lifecycle

·     Author or contribute to user and functional requirements, interface specifications, data mappings, configuration specifications, test scripts, traceability matrices, technical reports, SOPs, work instructions, and support documentation.

·     Plan and execute unit, functional, integration, negative, alarm, recovery, performance, security, and user-acceptance testing for assigned deliverables.

·     Support FAT, SAT, IQ, OQ, PQ, software qualification, interface qualification, and workflow comparability activities, as applicable to system impact and intended use.

·   Support end-to-end testing of automation, data, MES, electronic batch record, and related cGMP-system interfaces, including identity, status, parameter, exception, audit-trail, and record-transfer scenarios applicable to the intended use.

·     Document defects, deviations, investigations, corrective actions, change assessments, release evidence, and verification of resolution.

·     Apply cGMP, data-integrity, 21 CFR Part 11, computerized-system lifecycle, records-management, and change-control expectations where applicable.

·     Maintain accurate, complete, reviewable, and inspection-ready technical records.


Operational Support, Reliability and Continuous Improvement

·     Provide hands-on support during integration, testing, engineering runs, workflow deployment, and early operational use.

·     Use logs, equipment telemetry, event streams, issue trends, and user feedback to improve real-time monitoring, manufacturing observability, reliability, performance, recovery, predictive maintenance, and maintainability.

·     Develop troubleshooting guides, runbooks, support procedures, training materials, and knowledge articles for users and support teams.

·     Contribute to monitoring, alerting, incident triage, problem management, preventive actions, and planned lifecycle upgrades.

·     Communicate technical status, risks, dependencies, decisions, and recommendations clearly to project leads and cross-functional stakeholders.

External Partner and Vendor Collaboration

·     Work with robotics, instrument, software, cloud, and systems-integration vendors to clarify requirements, review designs, resolve technical issues, and verify deliverables.

·     Review vendor APIs, interface documentation, release notes, data models, test evidence, cybersecurity information, and configuration packages.

·     Participate in technical workshops, design reviews, FAT/SAT activities, commissioning, and support-transition planning.

·     Promote open, documented, and maintainable interfaces that reduce vendor lock-in and improve long-term supportability.


Required Qualifications

Education and Experience

·     BS or BA with 3+ years of relevant experience in Computer Science, Software Engineering, Data Engineering, Computer Engineering, Automation Engineering, Robotics, Bioengineering, Information Technology, or a related discipline

·     M.S. in a related discipline with 1+ years of relevant experience.

·     Equivalent combinations of education and directly relevant technical experience may be considered.


Technical Skills

·     Hands-on experience developing or supporting software, data, integration, or automation solutions in robotics, laboratory, manufacturing, or other technical environments.

·     Proficiency in at least one general-purpose programming language such as Python, C#, C++, or Java, plus practical SQL experience.

·     Experience with APIs, middleware, databases, message or event integration, data pipelines, software interfaces, or equipment connectivity.

·     Working knowledge of modern software-development practices and Digital- and IT-approved technology stacks, including source control, branching and peer review, automated testing, CI/CD concepts, APIs, containerized applications, cloud-development concepts, debugging, documentation, configuration management, and software release management.

·     Ability to diagnose issues spanning software, data, networks, hardware interfaces, equipment behavior, and user workflows.

·     Ability to translate scientific or operational needs into clear technical requirements and testable acceptance criteria.

·     Working knowledge of data modeling, metadata, lineage, provenance, audit trails, and data-quality controls.

·     Ability to collaborate effectively with Digital and IT on enterprise architecture, cybersecurity, identity and access, infrastructure, deployment, and supportability.

·   Experience or demonstrated ability to bridge OT, LT, and IT environments and support interoperability among robotics, laboratory systems, manufacturing systems, and enterprise platforms.

·     Ability and willingness to work hands-on in laboratory and engineering environments, including equipment setup, workflow execution, sample or material handling, testing, troubleshooting, and documentation.

·     Ability to follow laboratory safety, procedural, training, data-integrity, and quality requirements while supporting development and testing activities.

·     Clear technical writing and communication skills.

Preferred Qualifications

·     Experience with integrated laboratory or manufacturing robotics, orchestration software, scheduling systems, connected instruments, or automated material handling.

·     Experience with Multiply Labs Integrated, HighRes Biosolutions, Hamilton, Cellario, or comparable automation ecosystems.

·     Experience integrating robotics or automation platforms with LIMS, ELN, MES, electronic batch records, process historians, data lakes, cloud platforms, manufacturing analytics, or enterprise systems supporting cGMP operations.

·   Experience bridging OT, LT, and IT environments and aligning laboratory and manufacturing automation with enterprise architecture, cybersecurity, infrastructure, data, and operational-support models.

·   Experience deploying, scaling, transferring, commissioning, qualifying, or supporting manufacturing-ready automation for clinical or commercial production environments.

·     Experience working with enterprise-approved software stacks and lifecycle platforms such as Git-based repositories, Azure DevOps or comparable tooling, CI/CD pipelines, containerized applications, cloud services, infrastructure-as-code concepts, automated test frameworks, observability, or DevSecOps practices.

·     Experience with time-series data, event-driven architectures, OPC UA, MQTT, REST APIs, relational or NoSQL databases, or streaming data.

·     Experience in biotechnology, pharmaceuticals, biologics, cell therapy, gene therapy, or another regulated environment.

·     Familiarity with GAMP 5, 21 CFR Part 11, data integrity, computerized-system validation, risk assessment, and change control.

·     Experience with AI/ML-enabled engineering applications, including computer vision, image analysis, barcode or label recognition, object detection, robotic guidance, automated inspection, anomaly detection, predictive maintenance, optimization, or model monitoring.

·   Experience with digital twins, simulation environments, robotics or process modeling, workflow emulation, virtual commissioning, capacity modeling, or advanced workflow-optimization tools.

·     Hands-on experience executing laboratory studies, engineering runs, workflow characterization, equipment testing, or automation feasibility activities in a biological, analytical, or process-development laboratory.

·     Experience supporting equipment deployment, technology transfer, FAT/SAT, commissioning, validation, manufacturing readiness, or QC laboratory automation.


Work Environment

·     Hybrid role based in Tarzana, California, with regular onsite presence to perform hands-on laboratory testing and support robotics integration, software deployment, equipment setup and operation, engineering runs, workflow testing, troubleshooting, and collaboration with scientific and engineering teams.

·     Ability to work in laboratory, engineering, and manufacturing-support environments, subject to applicable safety, gowning, training, and access requirements.

·     Ability to work across global time zones and travel as needed for vendor workshops, FAT/SAT, technology transfer, and deployment support.

·     AstraZeneca expects employees to work from the office, on average, a minimum of three days per week while maintaining appropriate flexibility based on business, team, and individual needs.


Compensation and Benefits

The annual base pay for this position is expected to range from $90,024.00 - $135,036.00. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer eligibility for various incentives, including an opportunity to receive short-term incentive bonuses and equity-based awards for salaried roles. Benefits offered include qualified retirement programs, paid time off (including vacation, holidays, and leaves), and health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans.


Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, the employee will be in an at-will position and the Company reserves the right to modify base pay, as well as any other discretionary payment or compensation program, at any time, including for reasons related to individual performance, Company or department performance, and market factors.


Why AstraZeneca

At AstraZeneca, we are building the next generation of cell and gene therapy capabilities by combining process science with robotics, software, data, digital twins, computer vision, and responsibly governed AI. This role offers the opportunity to create the digital connective tissue that allows robotic systems to operate reliably, generate trusted data, and scale from laboratory development into manufacturing-ready automation and future commercial production environments.


You will work directly with scientists, automation engineers, Digital, IT, Quality, Manufacturing Operations, and external technology partners to solve practical integration and deployment challenges. Your work will help connect OT, LT, and IT environments; advance robotic cell therapy manufacturing platforms such as Multiply Labs; integrate automation with MES and related cGMP systems; and strengthen scalability, workflow reliability, data traceability, cybersecurity, supportability, and readiness for future AI-enabled commercial operations while preserving human accountability and regulated-system discipline.


Are you ready to bring new insights and fresh thinking to the table? We have one seat available, and we hope it is yours. Apply today.

Date Posted

08-Oct-2026

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

How we rate this

Digital Eng, Robotics & Automation, Process Sciences, Analytics and Technology, CGT at AstraZeneca rates 24 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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