Lead Site Reliability Engineer

Role Description

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.

Qualifications

• 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.

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.

Benefits

• High-impact role at the intersection of cloud infrastructure and financial technology — your work directly underpins products managing hundreds of billions in AUM.
• Significant growth potential: opportunity to help shape the SRE practice and prepare the platform for exponential scale.
• A promising technology roadmap spanning capacity planning, Kubernetes migrations, and service-oriented architecture modernization.
• Collaborative, engineering-driven culture that values quality, curiosity, and ownership.
• Competitive compensation and benefits package.