Senior Applied Platform Engineer

Genmab•Princeton, TX

1d•Onsite

About The Position

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees. Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so. Does this inspire you and feel like a fit? Then we would love to have you join us! Role Overview: Genmab continues to push the boundaries of innovation with an expanding portfolio of development initiatives in 2026, including multiple AI/ML and GenAI projects. We are seeking a Senior Applied Platform Engineer who will operate as a Forward Deployed Engineer (FDE) and will embed directly with business stakeholders to develop, implement, customize, and operationalize complex solutions in production environments. This is a strategic role that will work across diverse Genmab business domains including: Clinical Development TechOps AI Labs & Innovation Translational and Quantitative Science (TQS) Research & Discovery Legacy Solution Migration Unlike typical engineering roles, this position allows you to work at the front lines across diverse domains to understand their workflows, challenges, and opportunities firsthand. Your mission is to deliver immediate value through rapid prototyping, deployment, and feedback loops, solving unique, domain-specific problems that require deep understanding of both the technology and the business context. Additionally, as a Forward Deployed Engineer you will act as a critical bridge between real-world business needs and development and shaping roadmaps within our core platform teams. This is a hands-on, high-expectation, high-impact role requiring extraordinary generalist technical skills across AI/ML, MLOps, cloud computing, and DevOps domains combined with exceptional customer empathy, clear communication skills, and the agility to context-switch between different stakeholders, technologies, and business challenges. You must be comfortable working autonomously in ambiguous situations, making pragmatic technical decisions, and delivering production-ready solutions under tight timelines. Hub-and-Spoke Collaboration Model You will operate within our hub-and-spoke model, where you serve as the crucial link between centralized platform teams (part of the hub) and diverse business units (spokes). As a forward deployed engineer, you'll spend significant time embedded with business stakeholders, understanding their specific needs, constraints, and success metrics, then rapidly delivering tailored solutions while ensuring they leverage platform capabilities and integrating seamlessly with enterprise-wide platform standards. This role is based out of our Princeton office and requires for you to be on site 60% of the time You will be embed with multiple domain specific teams to ideate, develop, architect and deploy solutions that work within their unique infrastructure, data, AI/ML, and regulatory requirements (i.e. GxP and non-GxP environments). Your insights from these engagements will flow back to improve our core platform and inform strategic roadmap decisions.

Requirements

Master's or Ph.D. in Computer Science, Mathematics, Engineering, Physics, Chemistry, Statistics, or a related/adjacent field
4 + years of experience in AI/ML, cloud engineering, data science, infrastructure, MLOps, and/or DevOps (bonus if in healthcare, biotech, or life sciences domains)
Demonstrated experience working directly with business stakeholders or customers to deliver technical solutions
Proven track record of deploying production systems that delivered measurable business value
Strong programming skills in one or more languages such as Python, R, C/C++, Java, Go, Rust, etc.
Broad experience within the AWS cloud-service ecosystem
Deep expertise in AI/ML and GenAI frameworks such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers
Some knowledge of commonly used data platforms (e.g. Databricks, Snowflake, or Lake Formation) and tools (e.g. dbt) and their underlying technologies (e.g. Delta, Iceberg, Hudi, Spark)
Experience building and scaling AI-powered systems or applications in diverse domains
Proven experience in MLOps, including model deployment, versioning, monitoring, and drift detection
Strong knowledge of Generative AI, AI Agents, LLM fine-tuning, and NLP-based solutions for commercial use cases
Significant experience implementing IaC (Terraform, OpenTofu, CDK, Pulumi, etc.) + CI/CD for deploying cloud-based platform infrastructure at scale
Deep knowledge of containerization (e.g. Docker, Podman, etc.) and orchestration tools (e.g. Kubernetes, Rancher, etc.)
Experience with large scale CPU, GPU and/or multi-GPU infrastructure (bonus for CUDA fundamentals)
A basic understanding of life sciences business operations, including clinical, sales, marketing, research, commercial, market access, and revenue analytics
Ability to quickly understand complex business processes, identify pain points, and translate them into technical solutions
Understanding of data privacy, security, and regulatory requirements in healthcare and life sciences
Exceptional customer empathy: Ability to understand and advocate for customer needs while balancing technical constraints
Outstanding communication skills: Comfortable presenting technical concepts to non-technical audiences and business insights to technical teams
Entrepreneurial mindset: Self-driven, proactive, comfortable with ambiguity, and able to work autonomously
Adaptability: Flexible and open-minded when working with diverse stakeholders, accommodating various solutions, ideas, and challenges
Problem-solving orientation: Pragmatic approach to solving complex problems with imperfect information
Collaboration: Strong team player who builds trust and credibility across organizational boundaries
High ethical standards: Commitment to responsible AI practices in life science applications
Resilience: Able to handle the pressures of customer-facing roles and tight delivery timelines

Nice To Haves

Understanding of regulatory requirements in healthcare and/or pharma (GxP, HIPAA, GDPR, responsible AI standards)
Experience working in a hub-and-spoke model, balancing centralized initiatives with business unit needs
Flexibility and open mindset when working with stakeholders to accommodate a variety of solutions, ideas, and challenges
Strong product and development hygiene, with diligence in cost optimization of cloud resources and infrastructure

Responsibilities

Embed directly with business domain teams (Clinical, Research, Commercial, TechOps, Medical/Regulatory Affairs) to deeply understand their workflows, challenges, and success criteria
Rapidly prototype and deploy solutions that address specific customer needs, often involving unique data sources, AI/ML, GenAI, cloud infrastructure , and regulatory requirements
Act as the technical bridge between business stakeholders and core platform teams, translating real-world problems into technical requirements and vice versa
Build strong relationships with business users, providing hands-on technical guidance, training, and troubleshooting support
Gather and synthesize feedback from needs, processes, projects and solutions to inform platform improvements, feature prioritization, and product roadmap decisions
Champion customer needs within our engineering organization, ensuring platform development aligns with real-world use cases and delivers meaningful value
Build and deploy AI/ML models that support clinical operations, research, commercial functions, medical/regulatory affairs, TechOps, TQS analytics, forecasting, market intelligence, and real-world data insights
Architect, automate, and optimize AI pipelines on AWS and GitLab (SageMaker, Bedrock, Lambda, Step Functions, Redshift, Glue, S3, etc.)
Integrate Generative AI, AI agentic solutions, and LLMs into business workflows, enabling NLP-based insights, sales intelligence, and customer engagement strategies
Ensure AI solutions are scalable, robust, InfoSec-secured, and meet compliance standards (HIPAA, GDPR, responsible AI guidelines)
Partner with Platform Engineering to build and enhance MLOps, CI/CD, and customized Infrastructure as Code (IaC) pipelines
Implement application monitoring, logging, drift detection, and governance to ensure continuous improvement and compliance
Optimize workloads using distributed computing, GPU acceleration and/or serverless architectures
Support and integrate with data pipelines that connect Genmab datasets across clinical, commercial, research, medical/regulatory affairs, and TechOps from EHRs, claims data, real-world evidence (RWE), IQVIA, Symphony, and other biopharma sources
Enable seamless data access and processing across cloud storage, data lakes, and AI-driven solutions and applications
Work closely with Genmab business domain teams, business analysts, and data scientists to ensure AI models deliver business-relevant, high-impact insights
Act as the bridge between centralized teams (hub) and Genmab business stakeholders (spokes), ensuring alignment, performance, and business impact
Drive cross-functional collaboration, ensuring insights are actionable and operationalized at scale
Provide technical mentorship and leadership in solution delivery, ensuring best practices are followed
Stay abreast of the latest advancements in AI/ML, GenAI, cloud computing, and DevOps
Experiment with emerging AI/ML and GenAI technologies (LLMs, AI Agents, multi-modal AI, AutoML, RAG-based systems, etc.) to enhance Genmab's AI efforts
Champion a data-driven culture, advocating for AI-first approaches in business domain decision-making

Benefits

401(k) Plan: 100% match on the first 6% of contributions
Health Benefits: Two medical plan options (including HDHP with HSA), dental, and vision insurance
Voluntary Plans: Critical illness, accident, and hospital indemnity insurance
Time Off: Paid vacation, sick leave, holidays, and 12 weeks of discretionary paid parental leave
Support Resources: Access to child and adult backup care, family support programs, financial wellness tools, and emotional well-being support
Additional Perks: Commuter benefits, tuition reimbursement, and a Lifestyle Spending Account for wellness and personal expenses

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