Top Senior Site Reliability Engineer Jobs in Boston, MA

Leads the design and development of AI-driven enterprise and cloud security solutions. Manages teams delivering data, analytics, and machine learning engineering projects; oversees AI model implementation, data infrastructure, pipelines, and platform deployments. Uses Python and C++ for algorithm development, analyzes data, improves data quality, ensures technical compliance, mentors staff, manages client expectations, and drives innovation across cybersecurity and privacy initiatives.

Leads teams designing and deploying AI-driven enterprise and cloud security solutions. Responsibilities include developing machine learning systems, integrating data infrastructure and pipelines, performing advanced modeling and analysis, and building AI applications with Python, Java, and C++. The role involves client engagement, strategic problem-solving, stakeholder validation, coaching, process innovation, and operational excellence while addressing complex cybersecurity and privacy challenges.

Lead long-term strategy and architecture for cloud and on‑prem platform infrastructure, driving Kubernetes and multi‑cloud reliability, IaC/GitOps automation, observability, SLO/SLI/error‑budget practices, incident leadership, AI‑augmented tooling adoption, and mentorship of senior engineers to improve platform resilience and developer experience.

Manage AWS and GCP cloud environments, scale infrastructure globally, shape technical architecture, and build reliable CI/CD pipelines. Automate security and compliance controls, improve infrastructure performance, and develop systems interacting with smart contracts across multiple blockchains. The role requires Terraform, shell scripting, GitHub Actions, Docker, production cloud operations, and observability experience, with Kubernetes, networking, and fintech compliance knowledge preferred.

Build and operate reliable, scalable production infrastructure for GitLab’s user-facing services. Responsibilities include developing infrastructure automation and tooling, managing Kubernetes deployments, maintaining infrastructure as code, supporting CI/CD and GitOps, participating in on-call and incident response, improving observability and SLOs, troubleshooting production systems, and documenting operational practices. The role spans Intermediate through Senior Staff levels and requires strong software engineering, cloud, reliability, and asynchronous collaboration skills.

Owns resilience, performance, scalability, and operational cost improvements for a cloud-native platform. Designs and delivers full-stack solutions, builds monitoring and analysis capabilities, performs architectural and code reviews, and resolves complex production issues. The role requires pragmatic modernization judgment, AI-assisted development experience, customer or user accountability, and participation in a weekend on-call rotation.

Build and operate reliable cloud infrastructure, developer platforms, CI/CD systems, observability, and production workloads. Support applications, data systems, ML pipelines, and AI workloads across development, staging, and production. Establish SLOs, monitoring, incident response, automation, infrastructure-as-code practices, and operational standards. Collaborate with Product Engineering, Data Engineering, Data Science, and Security while mentoring engineers and participating in support rotations.

As a Senior Site Reliability Engineer, you'll design and build complex systems, support Atlas platform operations, automate processes, and ensure high availability of services.

Leads reliability standards across Infrastructure Engineering by developing Service Level Objectives, Service Level Indicators, error budgets, observability reporting, and reliability measurement practices. Partners with engineering teams to connect infrastructure performance to application and customer experiences, analyzes distributed-system failure modes, and influences teams through technical guidance, mentoring, and communication with senior leadership.

Lead SRE ownership of ML platform SLOs and operational health for Ray on EKS and Databricks on EC2. Maintain observability with CloudWatch/Datadog, tune autoscaling and GPU scheduling, manage Databricks workspaces and IAM, optimize cost/capacity, codify infrastructure with Terraform and CI/CD, lead incident response and postmortems, perform security/OS maintenance, and participate in on-call rotation.

Develop and maintain reliable platforms through automation, observability, incident response, performance optimization, and infrastructure improvements. The role collaborates with engineering teams, supports 24x7 reliability rotations, troubleshoots complex issues across code and infrastructure, and improves operational processes. Required experience includes SRE or equivalent work, software development, cloud platforms, monitoring, databases, and containerization. Preferred skills include Terraform, REST APIs, Grafana, Splunk, Agile, and GitOps.

Architect, develop, test, and distribute software, services, and infrastructure supporting Akamai’s cloud hypervisor platforms. Improve observability, automate infrastructure processes, troubleshoot complex distributed-system issues, mentor engineers, and participate in on-call service restoration. The role requires deep Linux, kernel, virtualization, ARM hardware, large-scale infrastructure, DevOps, and configuration-management expertise.

Build and operate Kubernetes-based platform infrastructure, infrastructure-as-code workflows, datastore services, and self-service platform capabilities. Collaborate with application teams on platform consumption patterns, diagnose datastore performance issues, contribute to architectural standards and code reviews, and support distributed systems using cloud services, Kafka, observability platforms, and relational or NoSQL databases.

Architect, build, and support reliable network infrastructure and automation for Akamai’s distributed cloud platform. Develop Bash and Python tooling, establish deployment standards, define SLOs, mentor engineers, and troubleshoot complex network issues. The role requires expertise in large-scale distributed systems, TCP/IP, BGP, Linux networking, configuration management, CI/CD, and open-source networking software, with participation in on-call rotations.

Lead design, build, and evolve developer infrastructure and CI platforms for Meraki cloud teams. Guide complex troubleshooting, mentor engineers, drive operational excellence, define roadmaps with leadership, and champion sustainable on-call practices while supporting large-scale distributed systems and automation across developer environments.

The Senior Site Reliability Engineer ensures SaaS platforms remain reliable, performant, secure, and scalable. Responsibilities include building cloud infrastructure, implementing monitoring and alerting, automating operational runbooks and deployments, managing Infrastructure as Code, applying AI-powered observability and remediation, supporting Kubernetes and cloud networking, and leading incident triage and root-cause analysis during 24/7 on-call rotations.

Develop, monitor, and maintain distributed production systems and AWS-based microservices infrastructure. Build automation, tooling, and repeatable processes that improve uptime, scalability, security, and operational efficiency. Support product engineering teams with performance, scaling, incident diagnosis, and production debugging. Analyze and tune systems, code, and networking while participating in on-call operations and blameless post-mortems.

Deploys and operates scalable, highly available cloud systems; improves application and network security, stability, speed, and capacity; automates cloud deployments; monitors and troubleshoots services to meet SLAs; analyzes logs and events; manages large-scale cloud infrastructure; and resolves infrastructure issues.

Build and maintain the Zero Touch Platform: develop Temporal workflows and Go services to automate cloud operations, own production systems (SLOs, on-call, incidents), debug cloud-native distributed systems, create CI/CD and IaC automation, and produce documentation to enable self-service across engineering teams.

The Senior Site Reliability Engineer will develop and support distributed storage services, ensuring reliability and operational safety, with a focus on automation and efficiency.

Own reliability, scalability, security, observability, and incident response for production applications across AWS and on-premises DoD environments. Build monitoring and alerting, define SLIs and SLOs, lead post-incident reviews, automate infrastructure with Terraform and Ansible, operate Kubernetes clusters, embed RMF and STIG controls, reduce operational toil, and support secure air-gapped deployments.

Internship SRE role responsible for availability, performance, and scalability of an e-commerce supply-chain platform. Tasks include SLO/SLA definition, observability (Prometheus/Grafana/Loki/Tempo/OpenTelemetry), incident response, capacity planning, disaster recovery for PostgreSQL, infrastructure-as-code (Terraform), CI/CD automation, and operational reliability for AI agent services. Mentored by Head of Technology/CTO with potential conversion to full-time based on performance.

Build and operate reliable, observable backend systems across AWS and Python services. Responsibilities include defining SLOs and error budgets, designing monitoring and alerting, managing incident response and 24/7 on-call rotations, conducting postmortems, improving performance and capacity, automating toil reduction, maintaining infrastructure as code and deployment pipelines, and mentoring SRE engineers. The role also involves consulting with client teams, documenting operational practices, and supporting AI workloads.

Lead reliability engineering for Replit’s large-scale infrastructure by designing observability, defining SLOs and SLIs, leading incident response, automating operations, optimizing Kubernetes and GCP deployments, debugging distributed systems, and mentoring engineers. Build internal tools and integrations in Python or Go, maintain infrastructure as code and CI/CD pipelines, improve system performance and resilience, and establish reliability, security, and operational best practices across the engineering organization.

Develop and operate Arista’s FedRAMP CloudVision SaaS platform at scale. Responsibilities include improving reliability, scalability, observability, autoscaling, disaster recovery, capacity planning, CI/CD, network architecture, cost optimization, and cloud application security. The role develops and manages Kubernetes-native services, distributed databases, and automation using technologies such as GCP, GKE, Go, Python, Ansible, Pulumi, and Bash. Participation in a FedRAMP on-call rotation is required.