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Senior, niche AI-infrastructure role reduces applicant density despite known employer.
Highly specialized AI infrastructure, GPU, vector DB, and Go/Kubernetes expertise limits cross-industry transferability.
Explicit 8+ years requirement and numerous mandatory tech stack items create high filtering.
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Develop and maintain internal platform APIs and tools enabling AI-ready environment provisioning for software engineers.
Build automated AI agents and event-driven pipelines using Go, Python, Kafka/RabbitMQ to support AI applications and infrastructure scaling.
Ensure reproducible, synchronized AI model deployments with Docker and Kubernetes, managing GPU workloads and vector DB storage infrastructure.
8+ years of experience in Platform Infrastructure Engineering with focus on AI application development.
Strong proficiency in Go and Python programming languages.
Experience with Kubernetes, Docker, distributed systems, Kafka or RabbitMQ, and vector databases/Redis.
Practical knowledge of Retrieval-Augmented Generation (RAG), prompt engineering, and LLM API integrations (OpenAI, Anthropic, Ollama).
Technical expert in event-driven, high-concurrency Go services supporting AI infrastructure and dynamic scaling.
Experienced in Kubernetes cluster extension and management focused on AI workloads including GPU and specialized storage.
Practitioner of code-first infrastructure problem-solving with emphasis on operational resilience, security-as-code, and observability tools (Prometheus, Grafana).