We are looking for a Senior Platform Engineer to join our engineering team. This is a hybrid role sitting at the intersection of backend software development and infrastructure engineering. You will own the design and delivery of platform capabilities - from backend services and APIs to the internal developer tooling, CI/CD systems, and Kubernetes-based infrastructure that power our engineering organization.
You will partner closely with software engineering teams, acting as both a builder and an enabler: shipping production-quality backend services while also raising the bar for developer experience, deployment reliability, and infrastructure scalability.
What You'll Be Doing
Design, build, and maintain production-grade backend services, APIs, and microservices.
Develop background workers, event-driven systems, and async processing pipelines.
Define and enforce backend architecture patterns - API design standards, service boundaries, data modeling, and error handling.
Collaborate with product and feature teams to deliver shared platform services (auth, notifications, integrations, etc.).
Integrate and operate AI agents within engineering workflows, using them as active development tools to accelerate delivery and improve code quality.
Contribute to the design and development of corporate AI-agent tooling - building the infrastructure, APIs, and platform abstractions that power our internal LLM-based tools.
Work closely with large language models (LLMs) - including prompt engineering, API integration, and building reliable pipelines around model inference.
Own and evolve our Kubernetes infrastructure, including Helm chart management, workload configuration, RBAC, and cluster operations.
Design and manage CI/CD pipeline templates shared across engineering teams - covering build, test, security scanning, and deployment stages.
Develop internal developer platform tooling that improves self-service capabilities and deployment velocity.
Drive observability best practices using tools like Datadog, OpenTelemetry, and Prometheus.
Requirements: What We're Looking For
6+ years of backend engineering experience with strong proficiency in Python and/or TypeScript / Go / Java.
Hands-on experience with Kubernetes - beyond basic deployments; you understand scheduling, resource management, networking, RBAC, and cluster-level operations.
Proven experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, or similar).
Strong background in designing and operating distributed backend systems, including microservices, message brokers (Pub/Sub, Kafka, RabbitMQ), and relational/NoSQL databases.
Experience developing internal developer tooling and platform abstractions.
Practical experience working with LLMs and AI agents - whether through API integrations (OpenAI, Anthropic, etc.), agentic frameworks (LangChain, LangGraph, CrewAI, or similar), or building tooling around model inference.
A DevOps mindset - you care about deployment safety, rollback strategies, and the lifecycle of code from commit to production.
Advantages
Experience with GitOps workflows (ArgoCD, Flux).
Experience with cloud platforms (GCP preferred, AWS).
Contributions to open-source infrastructure tooling.
Experience building or productionizing agentic systems, including tool use, memory, and multi-step reasoning pipelines.
Familiarity with LLM infrastructure concerns - model hosting, context management, cost optimization, or evaluation frameworks.
This position is open to all candidates.