Principal Software Engineer

About Reva.AI

Reva.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 Role

We 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 architec…