Senior Engineer

At Reltio®, an SAP Company, we believe data should fuel your success in the enterprise AI era. Our  Context Intelligence Platform turns fragmented data into a trusted, connected context so AI agents and systems can act with expert-level judgement at enterprise scale. Reltio’s cloud-native SaaS platform harmonizes, unifies, and governs data across sources and formats—including unstructured data—in real time, turning them into data assets that can be mobilized in milliseconds to any application, user, or AI agent. Trusted by more than 200 of the world’s largest brands across industries such as life sciences, financial services, healthcare, and technology, we fuel frictionless operations and help enterprises accelerate  innovation and reduce risk.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and industry and analyst recognition for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

We are seeking a Sr SDE – Reliability and Resiliency Engineering to drive platform reliability, resilience, and distributed systems robustness across the Reltio multi-cloud platform.

This is a hands-on engineering role focused on strengthening reliability practices, operationalizing chaos engineering, improving observability-driven validation, and embedding resilience into the software development lifecycle.

The ideal candidate has 5–8 years of experience building and operating distributed systems, good knowledge of multi-cloud environments (AWS, Azure, GCP), Kubernetes-based microservices, and the ability to contribute to resilience-focused design and engineering practices.

• Design and implement resilience strategies across AWS, Azure, and GCP environments.
• Support chaos engineering initiatives and integrate experiments into CI/CD pipelines.
• Validate RTO, RPO, SLO, and recovery objectives using metrics.
• Follow governance controls for chaos experiments.
• Identify and mitigate potential failure scenarios before production.

• Improve resilience across databases, caching, messaging, and auth services.
• Support multi-region and cross-cloud failover validation.
• Validate retry logic, circuit breakers, and graceful degradation.
• Reduce cascading failures and improve system stability.

• Use Grafana, Prometheus, and LogDNA for validation.
• Integrate reliability checks into Jenkins CI/CD pipelines.
• Ensure production readiness before releases.
• Use telemetry to identify improvement areas.

• Work with SRE, platform, and dev teams to improve resilience.
• Contribute to best practices and documentation.
• Participate in incident analysis and improvements.

• 6–9 years of software engineering experience.
• Experience with distributed systems and microservices.
• Exposure to AWS, Azure, and GCP.
• Hands-on Kubernetes experience (EKS, AKS, GKE).

• Strong Java and Spring Boot skills.
• Understanding of distributed system failures and resilience patterns.
• Exposure to chaos tools (Chaos Mesh, Gremlin, Harness, etc.).
• Knowledge of AWS, Azure, GCP services.
• CI/CD experience (Jenkins preferred).
• Understanding of SLOs/SLIs.
• Experience with Grafana, Prometheus, LogDNA.

• Exposure to multi-region architecture.
• Service mesh familiarity.
• Performance testing exposure.
• Security tools like Snyk.
• Good communication skills.

• Reliability checks integrated into CI/CD.
• Chaos testing improves resilience.
• Failures detected early.
• Improved system stability.
• Contribution to resilience-first culture.