Senior AI Engineer
Listed on 2026-07-19
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Software Development
AI Engineer (Applied/Software), Software Architect, Cloud Engineer - Software
Senior AI Engineer
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.
- 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.
- 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 Type Script.
- Hands‑on frontend engineering experience with Type Script/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…
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