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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.\nResponsibilities\nArchitect, build, and operate the internal LLM Gateway, including routing, rate limiting, quotas, cost tracking, and automated fallbacks.\nDesign and build the agent control plane, covering agent creation, context management, task execution, and state tracking.\nBuild and maintain internal SDKs to simplify LLM integration across teams.\nImplement platform observability, monitoring, alerting, tracing, and evaluation of LLM and agent workflows, including latency, token usage, costs, and failovers.\nImplement security and governance for LLM usage and AI agents.\nCollaborate with internal teams to translate business needs into working AI solutions and drive AI adoption.\nEvaluate build-vs-buy options and integrate relevant open-source tools where appropriate.\nRequirements\n5+ years of experience in backend development.\nStrong proficiency in Python or another modern backend language (Go, TypeScript, Rust), with a willingness to work with Python as our primary platform language.\nDeep understanding of distributed systems (async queues, rate limiting, retries, circuit breakers, failover mechanics).\nAt least 1 year of hands-on experience working with AI/LLM-based solutions.\nPractical experience with LLM APIs (OpenAI, Anthropic, Gemini): streaming, tool calling, context management, and rate limits.\nHands-on experience building AI agents or agentic workflows.\nSolid knowledge of observability (metrics, logs, tracing), \nExperience with Docker, Kubernetes, and Cloud (AWS or GCP).\nStrong logical thinking, high ownership, initiative, and product mindset.\nEnglish - Intermediate or higher.\nWill be a plus\nExperience building developer platforms, internal tooling, API Gateways, or SDKs.\nHands-on experience with MCP (Model Context Protocol), RAG pipelines, or vector databases.\nExperience with LLM observability and evals tools (Langfuse, LangSmith, OpenTelemetry).\nActive personal AI adoption (demonstrated use of AI tools/agents to automate own workflows).\nDegree in Computer Science, Software Engineering, or a related field.\nWe offer\n20 paid vacation days per year\n10 paid sick leave days per year\nPublic holidays as per the company’s approved Public holiday list\nMedical insurance\nOpportunity to work remotely\nProfessional education budget\nLanguage learning budget\nWellness budget (gym membership, sports gear and related 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