Job Description :

Who we are :

DigiCert is a global leader in intelligent trust.

We protect the digital world by ensuring the security, privacy, and authenticity of every interaction.

Our AI-powered DigiCert ONE platform unifies PKI, DNS, and certificate lifecycle management, to secure infrastructure, software, devices, messages, AI content and agents.

Learn why more than 100,000 organizations, including 90% of the Fortune 500, choose DigiCert to stop todays threats and prepare for a quantum-safe future at www.digicert.com.

Job summary :

We are building the trust layer for the agentic future.

As AI agents move from simple chatbots to autonomous workloads with access to sensitive enterprise data, the industry lacks a standard for Identity, Authentication, and Governance.

Our platform does not stop at application code.

It also creates and manages the secure cloud infrastructure in which AI-agent systems are deployed and operated.

That makes infrastructure design a core product capability, not a supporting function.

This role will lead the design and implementation of the multi-cloud platform that supports customer environments, secure deployment patterns, cloud networking, and production guardrails.

It is a hands-on principal engineering role for someone who wants to build the underlying infrastructure that makes secure AI-agent deployment possible at scale.

What you will do :

- Design and build backend services and APIs for onboarding, policy management, audit, environment inventory, and platform operations.

- Develop reliable and well-structured REST and gRPC APIs that power the management layer of a secure AI-agent platform.

- Own data models, service contracts, validation logic, and service-to-service interactions for core platform workflows.

- Work on integrations with cloud services, identity systems, and platform components that support secure runtime environments.

- Improve observability, error handling, test coverage, deployment safety, and production support for backend services.

- Collaborate with frontend, security, and infrastructure engineers to turn complex platform requirements into clear, maintainable backend implementations.

- Build services that will directly shape how customers manage AI agents in production, and support those services in production yourself.

What you will have :

- 8-12 years of backend engineering experience.

- Strong hands-on experience in TypeScript/Node.js, Go, Java, or Python ability to work across languages as the stack evolves.

- Strong experience designing and building REST and gRPC APIs, service integrations, and backend systems for production use.

- Good understanding of distributed systems concerns such as retries, idempotency, failure handling, observability, and release safety.

- Strong experience with relational databases (PostgreSQL, MySQL) and backend data modeling.

- Familiarity with event-driven patterns (queues, streams) is a plus.

- Experience with cloud platforms (AWS, GCP, or Azure) and secure backend integrations.

- Familiarity with ORM/query-builder tools, schema validation frameworks, and API specification standards (OpenAPI, protobuf).

- Nice to have : Experience with gRPC/protobuf service design, ORM tools (Prisma, TypeORM, SQLAlchemy), schema validation (Zod, Pydantic, JSON Schema), OpenAPI generation, cloud SDK integrations (AWS SDK, Google APIs), or message brokers (SQS, Pub/Sub, Kafka).

- Good to have : Experience with AI/ML managed services AWS Bedrock, GCP Vertex AI, or Azure OpenAI Service and familiarity with the infrastructure patterns they require (VPC endpoints, IAM, data residency, model routing).

Software Engineering Excellence :

We expect principal engineers to set the bar for code quality across the team.

This means writing clean, modular Terraform, well-structured shell and python automation, and production-grade Go where needed.

Strong testing discipline infrastructure integration tests, deployment validation, and adversarial failure injection and code that other engineers can operate and extend with confidence.

Startup Mindset :

- Comfortable operating in ambiguity.

- Experience owning architecture, implementation, and reliability simultaneously.

- Bias toward shipping and iterative improvement.

Benefits :

- Generous time off policies.

- Top shelf benefits.

- Education, wellness and lifestyle support.