Technical Lead - Site Reliability Engineer

About your role: Technical Leadership & Architecture Own and drive the technical direction for your team's infrastructure systems, making architectural decisions that balance reliability, scalability, and cost. Design systems of moderate to high complexity using distributed systems best practices; anticipate future use cases and minimize technical debt. Conduct architectural reviews and advance design patterns across the organization.

Identify and implement improvements to existing software architecture; define and expand design patterns to solve common platform problems. Define and enforce security best practices across team-owned systems; proactively surface gaps to senior leadership. Reliability & Operational Excellence Own the reliability posture of team-owned services — establish SLOs, monitor SLAs, and hold the team accountable to them.

Lead incident response for complex, multi-service issues; systematically debug, identify root causes, and ensure issues do not recur. Establish standards for logging, monitoring, and operationalization across all team-owned systems. Foresee potential operational issues and implement preventative measures to safeguard the customer experience.

Participate in and help lead the on-call rotation; ensure production systems are appropriately instrumented. Project & Delivery Ownership Act as DRI (Directly Responsible Individual) for medium-to-large SRE projects spanning months and involving cross-team collaboration. Partner with Engineering Managers and Product Managers to scope roadmap initiatives, break down work into actionable increments, and commit to delivery plans.

Negotiate scope effectively when required, ensuring adjustments align with customer needs and project goals. Proactively identify and resolve project risks — dependencies, architectural drift, and staffing blockers — before they impact delivery. What We Are Looking For Required Experience 7-10 years of experience in Site Reliability Engineering, DevOps, or Platform Engineering in a production cloud environment. 5+ years of hands-on experience with AWS cloud services across compute, networking, storage, and security. 5+ years managing Linux-oriented production environments at scale. 5+ years using Infrastructure-as-Code (Terraform, CDK, CloudFormation) and/or GitOps best practices. 3+ years operating and troubleshooting production Kubernetes environments. 3+ years applying AWS Well-Architected Framework principles across reliability, security, performance, and cost pillars. 3+ years in cloud security best practices including IAM, secrets management, network security, and compliance. 3+ years working with PostgreSQL in production: performance tuning, replication, backup, and recovery.

Demonstrated track record of leading multi-person technical projects from scoping through delivery. Technical Skills Strong general programming skills; comfort writing automation scripts and tooling in Python, Go, or similar. Deep knowledge of observability tooling — metrics, logging, distributed tracing — and how to use them to drive reliability.

Solid understanding of data retention, backup, and recovery processes across cloud-native systems. Experience with CI/CD pipelines, release management, and deployment automation. Familiarity with service mesh, API gateway patterns, and microservices architectures.

AI Fluency Experience using AI-assisted workflows across the SDLC, with an emphasis on production reliability, operability, and maintainability of large-scale systems (design, deployment, monitoring, incident response) Hands-on experience integrating LLMs or AI systems into production environments, with a focus on reliability, latency, observability, and failure handling (e.g., automated triage, incident copilots, runbook automation) Familiarity with agent-based or workflow automation systems applied to operational use cases such as alert triage, remediation loops, system diagnostics, or automated runbook execution Demonstrated ability to apply AI tools to improve system reliability, reduce MTTR, automate operational workflows, and enhance observability and alerting systems Working knowledge of LLMs, embeddings, RAG, and their operational constraints in production systems (latency, cost, drift, safety, and observability) Ability to identify opportunities where AI can meaningfully improve system reliability, on-call efficiency, incident response, and infrastructure automation Nice to have (SRE): Experience handling model degradation, fallback strategies, and cost anomalies Leadership & Collaboration Proven ability to lead technical discussions, drive alignment across engineering and product, and communicate decisions clearly to stakeholders. Experience mentoring junior and mid-level engineers in both technical skills and professional development. Able to operate independently with minimal supervision; comfortable making final technical decisions as DRI.

Strong communication skills in English — written and verbal — with experience influencing cross-functional partners. Thank you!