Next Step Systems
AI Backend Engineer, Work From Home
Remote AI Backend Engineer role with clear candidate location fit.
PostedJul 4, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
USA
Role overview
AI Backend Engineer, Work From Home
Requirements and responsibilities
Readable role content extracted into sections for faster review.
AI Backend Engineer Responsibilities:
- Build and operate backend systems that serve AI-powered insurance workflows in production.
- Design and implement AI orchestration layers that connect models, APIs, workflows, and business logic.
- Build inference pipelines for LLM-based and AI-assisted automation systems.
- Optimize latency, throughput, and cost across AI services (caching, batching, streaming, routing).
- Design stable service boundaries between backend systems, ML components, and product APIs.
- Implement observability: logging, metrics, tracing, alerting, and incident response workflows.
- Debug production issues across distributed AI systems and resolve root causes.
- Collaborate closely with frontend, product, operations, and ML teams to ship end-to-end features.
- Continuously improve system reliability, scalability, and performance.
AI Backend Engineer Outcomes:
- AI backend systems run reliably at scale with low latency and high availability.
- AI workflows are stable, observable, and production-ready across multiple products.
- System performance improves continuously through real-world feedback and optimization.
- Production incidents are quickly detected, diagnosed, and resolved.
- AI capabilities are seamlessly integrated into global customer and internal workflows.
AI Backend Engineer Qualifications:
- Strong backend engineering experience in production systems.
- Experience building or operating high-throughput, low-latency services.
- Familiarity with AI Systems (LLMs, Embeddings, or AI Workflows).
- Experience with distributed systems and production debugging.
- Strong understanding of APIs, data flows, and system design principles.
- Experience with observability tools (logging, monitoring, tracing).
- Strong ownership mindset and bias toward shipping.
- Comfortable working in fast-paced, globally distributed teams.
- Tech Stack: Anthropic, Artificial Intelligence (AI), Distributed Systems Tooling, Docker, Kubernetes, LLM APIs, Node.js, NoSQL, Observability Tools, OpenAI, Open-Source Models, Python, SQL.
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