Senior AI Engineer

ModernaTX • Cambridge, MA

6d • Hybrid

About The Position

Moderna is seeking a Senior AI Engineer in Cambridge, MA/ Warsaw, Poland to provide deep technical leadership for the design, implementation, and operation of AI software platforms and Cloud-based deployment patterns for Supply Chain and enterprise Digital. This is a senior individual contributor role that sets architecture, codes critical components, establishes engineering standards, and mentors engineers while partnering closely with product and business leaders. You will own end-to-end application architecture and delivery strategy for AI and data products: lakehouse patterns, Unity Catalog governance, CI/CD and release automation, MLflow model lifecycle, feature/data product packaging, model serving, vector search, observability, cost/performance optimization, and validated releases for GxP use cases. The role requires demonstrated experience shipping scalable AI/ML/GenAI systems, APIs, and data applications in enterprise environments.

Requirements

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, Applied Mathematics, Physics, or a related technical field; equivalent deep technical experience will be considered.
• 7+ years of software, data, or AI engineering experience, including 4+ years delivering production ML, GenAI, analytics, automation, or data-intensive systems.
• Expert proficiency with Python and SQL, strong software architecture fundamentals, and experience with at least one additional language such as Java, Scala, or TypeScript.
• Hands-on frontend engineering experience with TypeScript/JavaScript and a modern framework such as React, Angular, Vue, or Svelte, including reusable components, state management, forms, charts, browser fundamentals, accessibility, and responsive design.
• Hands-on backend engineering experience designing production APIs and services using Python, Node.js, Java, Scala, or comparable technologies, including REST/GraphQL patterns, service boundaries, authentication, authorization, testing, observability, and production debugging.
• Demonstrated experience architecting and operating LLM/GenAI systems, including RAG, agents/tool use, embeddings/vector search, model and prompt evaluation, guardrails, monitoring, and human-in-the-loop controls.
• Strong background in cloud architecture on AWS, Azure, or GCP, including IAM, networking, secrets management, CI/CD, infrastructure-as-code, and production support models.
• Experience designing secure, compliant, auditable systems in regulated environments, with practical understanding of GxP, data integrity, validation documentation, and change control.

Nice To Haves

• Experience in life sciences, pharmaceutical manufacturing, supply chain, quality, or another regulated operational domain.
• Experience with SAP-centric supply chain data and integration patterns, including SAP ECC/S/4HANA, IBP, MM, PP, QM, SD, EWM/WM, MDG, BTP, or related analytics enablement.
• Advanced experience with Databricks Asset Bundles, Terraform or infrastructure-as-code, Databricks SQL, Feature Engineering/Feature Store, Vector Search, model monitoring, and lakehouse governance patterns.
• Applied expertise in forecasting, optimization, simulation, anomaly detection, scheduling, inventory, logistics, or decision intelligence methods.
• Track record of mentoring senior engineers, shaping engineering communities of practice, and influencing technical direction across global teams.

Responsibilities

• Define the technical strategy and reference architecture for AI software delivery, GenAI applications, agentic workflows, ML services, and cloud-based data/AI platforms.
• Lead end-to-end Cloud deployment standards across development, test, validation, and production environments, including workspace architecture, Delta Lake/Lakehouse design, Unity Catalog, Workflows/Jobs, MLflow, model serving, deployment automation, observability, and access governance.
• Build and review critical software components, APIs, orchestration patterns, model-serving interfaces, reusable libraries, and platform accelerators that enable teams to move AI prototypes into production reliably.
• Establish engineering practices for AI/ML/LLMOps, including automated testing, CI/CD, infrastructure-as-code, release management, model and prompt versioning, evaluation, monitoring, incident response, and rollback.
• Guide integration of SAP and enterprise data sources into trusted data products, feature pipelines, semantic layers, and decision-support services for Supply Chain, Quality, Manufacturing, Finance, and Digital stakeholders.
• Partner with product owners, architects, cybersecurity, quality, validation, and infrastructure teams to ensure solutions meet business outcomes, security expectations, GxP requirements, and enterprise architecture standards.
• Coach and mentor engineers across regions, raise the quality of design reviews and code reviews, and help build a practical AI/Data/Automation Center of Excellence with reusable standards and assets.
• Improve platform reliability, performance, cost efficiency, data quality, and developer experience through metrics, architectural guardrails, operational playbooks, and continuous feedback from users and support teams.

Benefits

• Competitive healthcare, plus voluntary benefit programs to support your unique needs
• A holistic approach to well-being, with access to fitness, mindfulness, and mental health support
• Family planning benefits, including fertility, adoption, and surrogacy support
• Generous paid time off, including vacation, volunteer days, sabbatical, global recharge days, and a discretionary year-end shutdown
• Savings and investments to help you plan for the future
• Location-specific perks and extras

What This Job Offers

• Job Type: Full-time
• Career Level: Senior