Principal Engineer, AI/Software Support, Pooled Screening Core

Johnson & Johnson

. Serve as the senior software and AI technical expert for Cell & Genetic Medicines high-throughput screening capabilities .

Posted 9/29/2026full-timeRemote • Pennsylvania • United StatesLead💰 $117,000 - $201,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable software architectures and AI-enabled capabilities for high-throughput screening in cell and genetic medicines. Proficient in integrating complex systems and fostering cross-functional collaboration to enhance scientific productivity and operational efficiency.

Highest-signal resume keywords

AI/ML IntegrationSoftware System DesignAWS ProficiencyData Pipeline DevelopmentStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringMachine LearningGenerative AIData ArchitectureAPI DevelopmentComputational ToolsHigh-Throughput ScreeningLaboratory AutomationData GovernanceScientific Metadata Standards

Soft Skills

Excellent CommunicationRelationship BuildingProject ManagementCollaborationMentoring

Tools & Technologies

Amazon Web ServicesBenchlingElectronic Laboratory Notebook Software

Industry Keywords

Cell TherapyDrug DiscoveryFunctional GenomicsBiotechnologyPharmaceutical

Tech Stack

Tools & technologies

AWS

About the role

Key responsibilities & impact

Serve as the senior software and AI technical expert for Cell & Genetic Medicines high-throughput screening capabilities
Define and implement scalable architecture connecting laboratory automation, analytical instruments, enterprise systems, scientific data, and user workflows
Build applications, APIs, data pipelines, computational tools, and user-facing visualization solutions for cell therapy discovery
Develop and deploy AI-enabled capabilities, including machine learning, generative AI, retrieval-augmented generation, and agentic workflows
Identify and prioritize software and AI opportunities that improve organizational effectiveness, scientific productivity, operational efficiency, and decision-making
Translate experimental processes and scientific questions into intuitive, maintainable, and reproducible digital solutions
Organize and contextualize screening data, construct information, assay metadata, and analytical outputs
Improve experimental planning, data quality, hit identification, candidate ranking, and knowledge capture
Establish engineering best practices for architecture, development, testing, documentation, version control, deployment, observability, security, and lifecycle management
Build cross-functional and cross-departmental partnerships across Discovery Research, IT, Business Technology, and other groups
Align stakeholders, clarify expectations, and communicate decisions, risks, tradeoffs, and progress
Influence technical direction without direct authority
Mentor scientists and engineers in software engineering, data architecture, and responsible AI use
Create a connected, data-driven screening environment that supports reproducible experiments and therapeutic candidate selection

Requirements

What you’ll need

Bachelor’s degree in computer science, software engineering, data science, computational biology, bioinformatics, engineering, or a related technical field, with significant relevant industry experience
Extensive experience designing and delivering complex software systems in scientific, engineering, biotechnology, pharmaceutical, or similarly data-intensive environments
Demonstrated experience integrating AI/ML or generative AI models into usable, production-quality software systems
Experience using Amazon Web Services (AWS), including provisioning and managing compute instances and working with Amazon S3 buckets for secure data storage, access, and transfer
Strong systems thinking and ability to understand scientific workflows and translate user needs into scalable technical solutions
Excellent communication, stakeholder management, and relationship-building skills
Ability to manage projects and expectations across organizational boundaries
Ability to work effectively in highly collaborative, multidisciplinary teams
Ability to travel approximately 10–15% annually
Preferred: advanced degree
Preferred: experience in drug discovery, cell therapy, functional genomics, high-throughput screening, or laboratory automation
Preferred: experience integrating robotic systems, analytical instruments, and automated data-generation platforms
Preferred: familiarity with high-dimensional biological datasets, FAIR data principles, scientific metadata standards, data governance, and regulated or highly controlled technology environments
Preferred: experience developing scientific applications, visualization tools, knowledge systems, workflow orchestration, or AI agents
Preferred: hands-on experience with electronic laboratory notebook software, especially Benchling
Preferred: experience embedded in laboratory-facing organizations and partnering directly with experimental scientists

Benefits

Comp & perks

Consolidated retirement plan (pension)
Savings plan (401(k))
Long-term incentive program
Vacation – 120 hours per calendar year
Sick time – 40 hours per calendar year; 48 hours for employees residing in Colorado; 56 hours for employees residing in Washington
Holiday pay, including Floating Holidays – 13 days per calendar year
Work, Personal and Family Time – up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member; 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year
Remote work arrangement
Approximately 10–15% travel to company sites