Principal Software Engineer

About Reva.AIReva.AI is building the unified access control and security plane for the modern agentic era. As enterprises deploy autonomous AI agents, LLM-powered workflows, and deeply interconnected cloud services, perimeter security breaks down. Reva.AI provides dynamic, intent-aware access governance, graph-based authorization, and real-time least-privilege enforcement across human, machine, and AI identities.

We operate at the convergence of high-throughput distributed systems, graph analytics, and AI agent runtime governance.

The RoleWe are seeking an exceptional, deeply technical Principal Software Engineer to serve as a cornerstone of our engineering leadership. This is not an armchair architecture role. You will be an active, hands-on builder who thrives in code, designs distributed platform primitives, tackles hard R&D problems, and debugs deep production edge cases across diverse runtimes.

You will drive the technical evolution of Reva.AI’s multi-tenant SaaS platform—navigating an ecosystem that spans Kubernetes, serverless, polyglot microservices, graph databases, and LLM orchestration layers. If you are a polyglot engineer who can write high-performance systems code in Java, Go or Rust in the morning, optimize a complex graph query in Neo4j by midday, and architect a multi-cloud deployment pattern in the afternoon, this role is built for you.

What You Will Do

• Hands-on Architecture & Implementation: Design, prototype, and implement mission-critical platform components, policy evaluation engines, and high-throughput ingestion pipelines using Go, Rust, Java, and Node.js.
• Polyglot Systems & Data Modeling: Own and optimize diverse data layers—leveraging Neo4j for identity and entitlement relationship graphs, PostgreSQL for transactional persistence, and MongoDB for flexible audit and metadata stores.
• Platform & DevOps Engineering: Champion cloud-native platform infrastructure across Kubernetes (EKS) and serverless primitives. Build resilient CI/CD pipelines, automated deployment strategies, and infrastructure-as-code patterns with a roadmap toward multi-cloud portability (AWS, GCP, Azure).
• AI & Agentic R&D: Spearhead technical investigations into the security of AI agents, fine-grained LLM runtime authorization, prompt/context governance, and agent protocol integrations. Rapidly prototype new platform capabilities from whitepapers or emerging standards into production-grade systems.
• Hard Troubleshooting & Reliability: Dig into distributed traces, memory leaks, concurrency locks, and latency spikes across the entire stack. Take an active lead in root-cause analysis and operational resilience.
• Technical Leadership & Mentorship: Partner directly with the founders and product teams to translate ambiguous vision into robust architectural blueprints. Raise the engineering bar via rigorous code reviews, design docs (RFCs), and mentoring senior engineers.

What We Are Looking ForCore Engineering & Polyglot Agility

• 10+ years of hands-on experience designing and operating complex, low-latency, distributed backend systems at scale.
• Deep polyglot proficiency: Demonstrated ability to jump across runtimes—mastery in at least two of Go, Rust, Java, with practical fluency in Node.js/TypeScript and modern frontend awareness (React).
• Strong computer science fundamentals: Concurrency patterns, cache coherence, distributed transactions, memory management, and asynchronous I/O.

Platform, Infra & DevOps Mindset

• Strong hands-on expertise with Kubernetes (workload orchestration, ingress controllers, service meshes, operators) and container internals.
• Production experience with serverless paradigms (e.g., AWS Lambda, event-driven architectures via SQS/Kafka/EventBridge).
• Solid foundation in automated provisioning (Terraform/OpenTofu), CI/CD engineering, and multi-cloud deployment patterns.

Data & Storage Mastery

• Hands-on experience with graph databases (e.g., Neo4j, Cypher query optimization, graph traversal algorithms) applied to real-world relationship mappings.
• Deep architectural and operational understanding of relational and document stores (PostgreSQL, MongoDB), including partitioning, indexing strategies, and query plan tuning.

AI Depth & R&D Capability

• Practical understanding of modern AI/LLM architecture: embeddings, vector retrieval, agent tool-calling protocols, prompt pipelines, and model evaluation.
• Intellectual curiosity and velocity to pick up emerging open-source technologies, run POCs, benchmark them, and integrate or discard them pragmatically.

Mindset

• High agency, founder-level accountability, and comfort navigating the zero-to-one and scaling phases of a high-growth SaaS platform.
• Strong written communication: able to produce clear, structured RFCs and lead high-signal technical discussions.

Good-to-Haves / Bonus Points

• Prior experience with enterprise authorization frameworks (RBAC, ABAC, ReBAC), declarative policy languages (e.g., Cedar, Rego/OPA), or identity protocols (OAuth2, OIDC, SAML, SCIM).
• Familiarity with agentic integration protocols (e.g., Model Context Protocol / MCP) and runtime security monitoring.
• Active contributions to open-source systems, security tools, or developer infrastructure projects.