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Onsite or remote • London+1💼 Full-time🗓 2026-06-25

Core

Design and develop high-performance APIs, backend services, and data pipelines for AI workflows, including AI agents and model deployment.

Role type

Senior IC backend engineer (AI infrastructure)

Builds

Production-ready AI services, data pipelines for unstructured data, and AI agent orchestration systems

Domain

AI/ML infrastructure, cloud-native systems, distributed computing

Deliverable

production ML models | infrastructure

Required skills

Golang, cloud infrastructure, container orchestration, API design, distributed systems, observability

Preferred skills

ML frameworks, AI agent technologies, message queues, zero-trust networking, serverless architecture

Technologies

GCP, AWS, Azure, Kubernetes, Docker

Responsibilities

Design and develop high-performance APIs and backend services for AI workflows; Build robust data pipelines to process large-scale unstructured data; Integrate LLMs, VLMs, and other ML models into production-ready services; Ensure system performance, observability, and fault tolerance in distributed environments; Partner with ML engineers and product managers to deliver end-to-end features; Help shape engineering culture and long-term architecture

Seniority

Senior, hands-on IC

Rewrite
## About the role As our Senior AI Backend Engineer, you'll build the core backend infrastructure that powers Instill AI's AI-native product experiences — from large-scale unstructured data processing to real-time AI agent orchestration. ## Responsibilities ### Build - Design and develop high-performance APIs and backend services for AI workflows, including AI agents and model deployment - Build robust data pipelines to process large-scale unstructured data (documents, audio, video) - Integrate LLMs, VLMs, and other ML models into production-ready, reliable services ### Engineer - Apply best practices in architecture and infrastructure, including IaC, microservices, serverless, API-first design, and Twelve-Factor principles - Ensure system performance, observability, and fault tolerance in distributed environments - Work with cloud platforms (GCP, AWS, Azure), Kubernetes, Docker, and modern observability tools ### Collaborate - Partner with ML engineers, product managers, and designers to deliver end-to-end features - Help shape engineering culture, best practices, and long-term architecture ## Requirements ### Must-haves - 7+ years experience in backend or infrastructure engineering - Strong proficiency in Golang (Go) - Proven track record building and scaling AI-powered or data-intensive systems (LLMs, RAG pipelines, agent-based architectures) - Solid understanding of cloud infrastructure and container orchestration (Kubernetes, Docker) - Experience ensuring scalability, resilience, and security in distributed systems ### Nice-to-haves - Familiarity with ML frameworks and AI agent technologies - Knowledge of message queues, zero-trust networking, and serverless architecture ### Mindset - Systems thinker with a passion for automation and reliability - Comfortable in a fast-paced startup environment with frequent releases - Excellent communicator with strong documentation skills - Customer- and data-obsessed with a high attention to detail - Proactive, self-driven, and curious about continuous improvement ## What's next If you're interested, please submit your application here!
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