Top Platform Engineer Jobs in Boston, MA

Design, build, and own the full data platform (ingestion, modeling, CI/CD, orchestration, observability, and BI). Implement streaming and batch pipelines for IoT data, enable governed self-service, enforce data governance/privacy/security, evolve AI access patterns, and provide technical leadership and mentorship to data engineers and data scientists to deliver production-ready analytics and ML capabilities.

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.

Designs and operates ServiceNow platform services and developer productivity tooling, embedding automation, CI/CD, container/runtime capabilities, security, and observability. Leads migrations, upgrades, incident response, and platform hardening. Automates provisioning, configuration, and compliance validations, documents standards and runbooks, mentors engineers, and supports critical escalations to improve reliability and developer experience.

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.

Provide 3rd-level support and engineering for end-user computing and mobility across corporate and retail. Design and document setup, installation, patching, and support processes. Test and deploy solutions (Intune, Autopilot, AVD, endpoint management), troubleshoot systems, analyze data for service improvement, collaborate with architecture and supplier partners, and drive continual service delivery enhancements.

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

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.

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.

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.

Partner with business teams to identify high-leverage AI opportunities; design, build, and ship agentic AI solutions and internal AI platform components. Deliver production LLM-based agents, integrations, and CI/CD pipelines while driving AI enablement, safety, and adoption across the company.

Own and operate OnRamp's AWS platform, IaC, CI/CD, and deployment tooling; build AI/agent execution infrastructure and observability; drive reliability, incident response, security/compliance, and automation using coding agents and LLM tools.

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

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Design, build, and operate AI platform components (LLM gateway, model serving, developer tooling). Own features from development to production, contribute to reliability, observability, governance, and cross-functional integration while producing technical documentation and participating in design reviews.

Build the core AI platform and high-performance Rust backend powering an AI-native trading copilot. Implement streaming responses, low-latency tool execution, caching, orchestration of models and tools, secure APIs, auditing/tracing, and safe, auditable trading action infrastructure. Partner with product and frontend to enable AI-native UX and translate trading domain requirements into resilient platform primitives.

Lead cross-team data platform initiatives focused on the Data Lake. Drive architecture and roadmaps for lakehouse storage, compute, orchestration, modeled data layers, and operational automation. Own large, complex programs end-to-end, make high-judgment architectural decisions, establish standards and paved paths, respond to incidents, and mentor senior engineers while aligning stakeholders across engineering, product, analytics, and AI/ML.

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.

Design and build an enterprise generative AI platform: agent orchestration, memory, guardrails, vector search, SDKs, and blueprints. Standardize agentic workflows, optimize orchestration and cost, own Helm/Kubernetes operators, ensure trust and safety, mentor engineering teams, and evangelize platform architecture internally and externally.

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.

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, build, deploy, and support foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and optimization. Partner with cross-functional teams to deliver scalable, performant, and responsible generative AI platform services and contribute to long-term technical vision and roadmap.

Design, build, and maintain full stack systems for WHOOP's design system and translation infrastructure, improving internationalization support and collaborating across teams.

The Senior Lead AI Engineer will develop AI software components, partner with cross-functional teams, and contribute to AI system optimization. Key responsibilities include model training, deployment, and leveraging AI technologies to enhance banking services.

Lead design, development, deployment, and support of scalable GenAI platform components (foundation model training, LLM inference, vector search, guardrails, evaluation, observability). Optimize training and inference performance, contribute to technical vision and roadmap, and partner with cross-functional teams to deliver responsible, production-grade AI systems.

The Cloud Platform Engineer will lead the delivery of the Flyways AI Platform, deploying, maintaining, and scaling secure cloud infrastructure while collaborating on coding software solutions with product engineers.