Principal Software Engineer, Privileged Access Management

Experience

1+ year of software engineering experience as a Principal Software Engineer with a SaaS company

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)