Saviynt’s Enterprise Identity Cloud helps modern enterprises scale cloud initiatives and solve the toughest security and compliance challenges in record time. We bring together Identity Governance (IGA), granular application access, cloud security, and Privileged Access Management (PAM) to secure the entire business ecosystem with a frictionless user experience. The world’s largest brands — including federal agencies and Fortune 500 financial institutions — trust Saviynt to accelerate digital transformation, empower distributed workforces, and meet continuous compliance.
WHAT YOU WILL BE DOING
Debug, optimize, and refactor existing services as we evolve toward multi-tenant, multi-cloud, federal-
ready
Serve as a technical expert for internal teams and, when needed, customer-facing escalations
WHAT YOU BRING
Experience
10+ years of software engineering experience with demonstrated ownership of complex system design, implementation, and technical decision-making
Track record of taking systems from design through production at scale, including multi-tenant SaaS
Security & Compliance
Hands-on experience building security-focused systems — Privileged Access Management, Identity Governance, Authentication, Secrets Management, or adjacent domains
Required knowledge of FedRAMP, FIPS 140-3, and GovCloud (AWS GovCloud or Azure Government) — what they constrain, why, and how to design within them
Working knowledge of modern cryptography in practice: TLS/mTLS, KMS-backed key hierarchies, envelope encryption, HSM/key vault integration
Languages & Programming
Go strongly preferred as the platform’s primary language; deep proficiency in at least one systems/services language (Go, Rust, C++, Java, or similar) is required
Polyglot capability — you can read, reason about, and contribute across multiple languages, and you can defend language-choice decisions on technical merit
Frontend literacy in TypeScript/React is a plus
Architecture & Infrastructure
Solid hands-on Kubernetes experience — EKS or equivalent, Helm, manifests, operators, day-2 operations. Not “I used kubectl apply once.”
Cloud platform proficiency on AWS or Azure; multi-cloud experience is a plus
Microservices and API design: REST, gRPC/Protobuf, and the trade-offs between them
Experience with event-driven architectures (message buses, async workflows) — you know when to reach for them and when not to
Workflow orchestration experience (Temporal or similar) is a plus
Relational database design at scale — PostgreSQL preferred; schema-per-tenant or comparable isolation patterns a plus
Engineering Practice
Strong testing discipline: unit, integration, end-to-end, and property-based testing
Infrastructure as Code: Terraform, Helm; GitOps (ArgoCD) a plus
CI/CD pipeline design and ownership — GitLab, GitHub Actions, Jenkins, CloudBees, or equivalent
Observability: OpenTelemetry, structured logging, metrics, tracing
Containerization: Docker multi-stage builds, distroless/minimal runtimes
AI-Driven Development
Active, deliberate use of AI coding tools (Claude Code, Cursor, Copilot, or comparable) as part of your daily workflow — beyond autocomplete
Comfort working in a spec-driven, agent-assisted development model with mandatory verification gates; AiDLC will be our SDLC, and we expect candidates to embrace and help refine it
Critical-review instincts: you don’t ship AI-generated code without reading it, testing it, and understanding it
Leadership
Demonstrated experience mentoring engineers and leading technical initiatives across distributed teams
Strong written and verbal communication — you can write a clear design doc, a clear PR description, and a clear engineering contract for an AI agent
Comfortable operating in a globally distributed organization (US + India)
Qualifications
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