Senior Engineer, SRE

At Zencoder.ai, we build and orchestrate AI agents that ship real work - code, research, operations, and more. What started as developer tooling is becoming a platform where people and agents collaborate across knowledge work tasks.

We’re looking for an Engineer to help build and operate the infrastructure behind Zencoder’s AI-powered products.

You’ll work across our production platform, improving its reliability, security, scalability and cost efficiency. This includes our Kubernetes foundations, cloud infrastructure, networking, data systems and the internal tooling that enables engineers to deploy and operate services confidently.

This is a hands-on engineering role rather than a traditional operations position. You’ll write code, automate infrastructure, investigate production issues and design systems that reduce operational complexity as the company grows.

The exact problems will evolve quickly. You should be comfortable taking ownership of unfamiliar systems, identifying the highest-leverage improvements and moving between immediate production needs and longer-term platform investments.

• Owning our Kubernetes foundations: building and operating production GKE clusters with reliable networking, ingress, service-to-service communication, workload isolation, autoscaling and deployment patterns.
• Improving cloud security and networking: evolving our GCP architecture across VPCs, IAM, workload identity, secrets, firewalls, WAF, CDN and other security controls.
• Building dependable search infrastructure: improving the deployment, scaling, performance and operational reliability of OpenSearch and other data-intensive systems.
• Reducing infrastructure cost: developing better cost attribution, capacity planning and optimisation across compute, storage, networking, observability and managed cloud services.
• Making deployments safer: improving CI/CD, GitOps, progressive delivery, automated rollback and the tooling engineers use to deploy and operate their services.
• Strengthening production reliability: improving observability, alerting, incident response, disaster recovery and the resilience of critical customer-facing systems.
• Automating operational work: replacing manual procedures with software, infrastructure-as-code and reusable platform capabilities.
• Preparing the platform for growth: identifying architectural bottlenecks and evolving our infrastructure to support increasing usage, larger customers and new AI workloads.

• You have strong software-engineering skills and regularly write production code.
• You have experience building and operating infrastructure on GCP, AWS or another major cloud platform.
• You have hands-on experience with Kubernetes in production.
• You understand cloud networking and security concepts such as VPCs, IAM, load balancing, firewalls, WAFs, CDNs, DNS and service identity.
• You have experience with infrastructure-as-code and automated deployment systems.
• You are comfortable debugging problems across application, infrastructure, networking and data-system boundaries.
• You have operated distributed systems such as OpenSearch, Elasticsearch, PostgreSQL or similar technologies at scale.
• Experience deploying or operating large language models with serving frameworks such as vLLM or SGLang is a plus, but not required.
• You care about reliability, security, developer experience and cost - not just whether infrastructure is technically running.
• You look for ways to remove operational toil rather than accepting repetitive manual work.
• You take ownership of important problems and are comfortable working across traditional team boundaries.

Experience with every technology we use is not required. We value strong engineering fundamentals, good judgement and the ability to learn unfamiliar systems quickly.