Site Reliability Engineer

Lead /

Senior – Site Reliability

Skills Required: SQL, NoSQL, Kubernetes, CI/CD, Splunk, Kafka, RMQ, MQ, SRE, Site Reliability

Experience Range: 8–10 Years

Job Description We don’t just build technology — we empower people. We believe in investing in growth, impact, and the future. Join a world-class engineering team focused on building and scaling intelligent infrastructure for LLM-based applications, AI services, and enterprise-scale backend systems. As a

Lead /

Senior Site Reliability Engineer , you'll contribute to the design and implementation of observability, automation, and incident response strategies that ensure platforms are high-performing, reliable, and cost-effective. You'll play a key role in driving operational excellence, supporting platform scalability, and collaborating across engineering and architecture teams. This role provides opportunities to influence large-scale architecture and AI/ML reliability.

What You'll Do

• Implement and maintain observability, monitoring, and alerting systems for AI platforms and mission-critical backend services serving the Supply Chain domain.
• Collaborate in designing telemetry pipelines, logging infrastructure, and metrics dashboards using tools such as Splunk, Prometheus, Grafana, and OpenTelemetry.
• Contribute to the development of SLOs, SLIs, and real-time health indicators across platform services and APIs.
• Participate in on-call rotations and lead resolution of high-impact incidents, including root cause analysis and postmortem reporting.
• Work closely with platform engineering teams to enforce governance, compliance, and security standards in production environments.
• Improve deployment pipelines, CI/CD workflows, and infrastructure automation (e.g., GitLab).
• Tune and scale infrastructure components such as Kafka, HAProxy, RMQ, databases, and distributed APIs.
• Support capacity planning, cost analysis, and system tuning to optimize platform performance.
• Advocate for automation-first operations, reducing toil through scripting and system reliability tooling.
• Contribute to documentation, runbooks, and knowledge sharing across SRE and engineering teams.
• Mentor junior engineers and foster a culture of technical rigor and continuous improvement.

What You'll Bring

• Bachelor's degree in Computer Science, Engineering, or a related field (Master's preferred).
• 8-15 years of experience in SRE, DevOps, or Operations Engineering in cloud-based environments.

Engineering & Operations

• CI/CD for integrations and infrastructure
• Automated testing (integration/regression)
• Performance and scalability engineering
• SRE fundamentals (SLIs, SLOs, RCA)
• Platform cost visibility and optimization
• Security-first design and compliance readiness
• Hands-on experience with monitoring, alerting, and incident response in distributed systems.
• Strong coding/scripting skills in Python, Java, or shell scripting languages such as Bash or PowerShell.
• Proficiency with CI/CD pipelines and GitLab workflows.
• Strong working knowledge of SQL and NoSQL databases, including Oracle DB and MongoDB.
• Working knowledge of AI/ML systems, APIs, and modern LLM tooling is a strong plus.
• Familiarity with observability tools such as Splunk, Grafana, and Prometheus.
• Experience with Kubernetes, container orchestration, and hybrid/multi-cloud environments (Azure, AWS, GCP, OCI).
• Demonstrated ability to work in fast-paced, incident-driven environments with high availability requirements.

Preferred Qualifications

• Experience supporting AI workloads, model inference systems, or LLM-enabled platforms.
• Exposure to AIOps or ML platform observability and reliability practices.
• Experience in highly regulated financial environments with an understanding of compliance and audit controls.
• Familiarity with platforms such as OpenAI or AI Gateway patterns.
• Background in building secure, zero-downtime platforms with enterprise-scale SLAs.

Must-Have Skills

• Strong understanding of SRE best practices, including SLOs, SLIs, postmortems, and chaos engineering.
• Proficiency in diagnosing system bottlenecks across infrastructure, application, and network layers.
• Experience driving automation across observability, configuration, and deployment domains.
• Experience integrating with OFSLL or Oracle Financial Services Lending and Leasing or third-party finance systems.
• Hands-on experience with OCI, OFSLL maintenance, and support.
• Strong communication and collaboration skills in cross-functional technical teams.
• Curiosity-driven mindset with a passion for learning emerging AI technologies and systems reliability.