Top Platform Engineer Jobs in Boston, MA

Lead design and build of an AWS-only AI Operations platform: hosting, IaC, registries (Accountability, Agent, Tool), identity/authorization patterns, developer DX, observability, and security hooks for agentic systems. Evangelize internally and partner on compliance and security integrations.

Lead operational design and engineering for the data platform: own Snowflake and dbt administration, automate platform operations and CI/CD, monitor platform health and observability, enforce governance and access, optimize performance and costs, and develop AI/agent integrations to enable governed data access for business users.

The role involves designing and managing secure cloud infrastructure on AWS, automating security practices, and collaborating with various teams to improve developer workflows and ensure compliance. Key tasks include IAM management, implementing automation tools, and participating in incident response.

Lead Workday functional engineer responsible for designing, configuring, and supporting Workday HCM modules (HCM, Recruiting, Compensation, Payroll, Benefits). Partner with product owners, provide production support, automate processes, maintain documentation, and drive process improvements and Workday upgrades.

The Platform Engineer IV will act as a MuleSoft SME, responsible for designing, developing, and implementing software solutions, mentoring junior engineers, and collaborating across teams to deliver quality outcomes.

Lead ownership and evolution of Dropbox's Windows endpoint platform (CorpFleet). Improve endpoint management, Intune workflows, security/compliance, automation, operational reliability, and cross-functional rollout. Mentor engineers and drive multi-phase platform initiatives, documentation, and runbooks to scale secure, reliable endpoint experiences.

The role involves building and improving WHOOP's data platform infrastructure, ensuring reliability and efficiency, and driving best practices across engineering and data workflows.

Design, build, and operate Jellyfish's Databricks Lakehouse and data/AI platform. Build ingestion, transformation, and delivery pipelines; govern data with Unity Catalog; enable BI, agentic analytics, metadata, lineage, and observability. Provide technical leadership, set architecture and standards, mentor peers, and collaborate with cross-functional stakeholders to make Databricks the foundation for analytics and AI.

Build and scale AI platform infrastructure for internal agents across AWS/GCP. Integrate identity (Okta, OAuth2/OIDC), implement agentic security, containerized deployments (Docker/Kubernetes), CI/CD and Terraform-based pipelines, run vendor evaluations, and design observability/telemetry for LLM-driven workflows while collaborating with security, identity, and engineering teams.

As a Lead Platform Engineer, you will develop solutions on Workday for HR, improve data quality, and lead integration teams. Collaborate with stakeholders to ensure cohesive system configurations and optimize business processes using Agile methodologies.

Lead a team to develop solutions in Workday Finance, focusing on automation and integration, while collaborating with stakeholders and improving business processes.

Technical leader responsible for cloud platform architecture, IaC, CI/CD, self-service developer tooling, reliability, observability, and cost optimization. Mentor engineers, drive automation, lead initiatives from design to production, and collaborate with Security and Operations on secure scalable solutions and incident response.

Design, build, and operate the core data warehouse, ingestion, orchestration, and cataloging platform. Develop batch and streaming pipelines, ensure data quality, governance, observability, and provide ML data platform capabilities. Lead architecture, improve platform reliability and performance, and collaborate with product, engineering, data science, security, and compliance teams.

Lead design, development, deployment, and support of large-scale AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Collaborate with cross-functional teams, optimize models for performance and cost, leverage open-source and SaaS AI tools, and shape the long-term technical vision for foundational AI platform services.

Lead design, development, and operation of WHOOP's Kubernetes clusters on AWS. Drive architecture to improve scalability, resiliency, performance, and security across the build/deploy platform. Build tooling for safer, faster Kubernetes deployments, advance CI/CD, mentor engineers, participate in incident response/postmortems, and partner with application, security, and data teams to embed secure-by-default practices and define the long-term infrastructure roadmap.

The role involves designing and operating AI systems, building data pipelines, fine-tuning models, and mentoring team members while collaborating with product and data science teams.

The role involves designing, developing, and supporting AI software components, leveraging various AI technologies, and optimizing performance for large-scale AI systems.

The Lead Platform Engineer will develop and manage Workday integrations, optimize HR technology, and lead a team while ensuring quality and innovation in various HR modules.

As a Senior DevOps Engineer at WHOOP, you will enhance application infrastructure to ensure high performance, scalability, and security while mentoring engineering teams.

As an Android Engineer II, you'll develop scalable design systems, support internationalization, maintain UI components, and enhance app performance while collaborating with design and backend teams.

The Software Engineer II (Frontend) will design and develop user experiences for WHOOP's digital products, focusing on responsive web applications and collaboration across teams.

As a Senior Software Engineer, you'll build scalable systems, collaborate with teams to deliver software features, and ensure high-quality applications.

Lead design, development, deployment, and support of production-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability). Drive LLM optimizations, technical vision, and cross-functional delivery of responsible AI products.

Lead design and delivery of an agentic AI platform: define architecture, standardize agentic workflows, build GenAI SDK/CLI, harden guardrails and observability, optimize orchestration and costs, own Helm/K8s operators for autoscaling, incubate RFCs and proofs of concept, and mentor engineering leaders while evangelizing platform practices internally and externally.

Design, build, and operate foundational platform services to improve availability, scalability, latency, and efficiency. Enable product teams via platform primitives (infra, databases, queuing), leverage Python, Go, AWS, Kubernetes, and Terraform, and mentor engineers to deliver resilient, scalable systems and improved developer experience.