Senior AI Platform Engineer

We are looking for a Senior AI Platform Engineer to build and own our company-wide AI platform from the ground up - a reliable, secure, and cost-transparent foundation that empowers every team to leverage LLMs and delegate work to autonomous AI agents. In this role, you will take full ownership of the platform’s core architecture and drive internal adoption across the entire company. You will lead the delivery of our internal LLM gateway as the single entry point for all model providers - complete with team quotas, cost tracking, and automated failovers - while establishing an observable shared platform with monitoring and alerting. In parallel, you will ship native internal SDKs for our primary tech stacks, deploy an Agent Control Plane enabling teams to orchestrate and track autonomous workflows, and partner directly with internal squads to turn high-impact business use cases into production-grade solutions.

Responsibilities
Architect, build, and operate the internal LLM Gateway, including routing, rate limiting, quotas, cost tracking, and automated fallbacks.
Design and build the agent control plane, covering agent creation, context management, task execution, and state tracking.
Build and maintain internal SDKs to simplify LLM integration across teams.
Implement platform observability, monitoring, alerting, tracing, and evaluation of LLM and agent workflows, including latency, token usage, costs, and failovers.
Implement security and governance for LLM usage and AI agents.
Collaborate with internal teams to translate business needs into working AI solutions and drive AI adoption.
Evaluate build-vs-buy options and integrate relevant open-source tools where appropriate.

Requirements
5+ years of experience in backend development.
Strong proficiency in Python or another modern backend language (Go, TypeScript, Rust), with a willingness to work with Python as our primary platform language.
Deep understanding of distributed systems (async queues, rate limiting, retries, circuit breakers, failover mechanics).
At least 1 year of hands-on experience working with AI/LLM-based solutions.
Practical experience with LLM APIs (OpenAI, Anthropic, Gemini): streaming, tool calling, context management, and rate limits.
Hands-on experience building AI agents or agentic workflows.
Solid knowledge of observability (metrics, logs, tracing),
Experience with Docker, Kubernetes, and Cloud (AWS or GCP).
Strong logical thinking, high ownership, initiative, and product mindset.
English - Intermediate or higher.

Will be a plus
Experience building developer platforms, internal tooling, API Gateways, or SDKs.
Hands-on experience with MCP (Model Context Protocol), RAG pipelines, or vector databases.
Experience with LLM observability and evals tools (Langfuse, LangSmith, OpenTelemetry).
Active personal AI adoption (demonstrated use of AI tools/agents to automate own workflows).
Degree in Computer Science, Software Engineering, or a related field.

We offer
20 paid vacation days per year
10 paid sick leave days per year
Public holidays as per the company’s approved Public holiday list
Medical insurance
Opportunity to work remotely
Professional education budget
Language learning budget
Wellness budget (gym membership, sports gear and related expenses)