# Senior Software Engineer — Infra Agent Systems

**Company:** [Together AI](https://hotfix.jobs/companies/together-ai)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** AI Agents, Distributed Systems, Backend Engineering, Knowledge Graphs, Information Retrieval, Kubernetes, Argo CD, Infrastructure As Code, Go, TypeScript, Python, Rust, Graph Databases, Kafka, Prometheus
**Posted:** 2026-08-25

> Build production AI agents and the distributed platform that operates large-scale GPU infrastructure. The role requires 5+ years of backend, distributed systems, or infrastructure experience, with expertise in agent systems, knowledge graphs, retrieval, or semantic search.

## Job Description

## Responsibilities
- Design and build production AI agent systems that diagnose, investigate, and remediate infrastructure issues across a large GPU fleet.
- Build distributed services, orchestration frameworks, knowledge graphs, and retrieval systems that power infrastructure agents.
- Develop fleet intelligence systems combining telemetry, infrastructure state, operational knowledge, and historical incidents.
- Integrate with observability, incident management, ticketing, fleet inventory, source control, chat, and internal infrastructure systems through APIs.
- Own services end to end, including architecture, implementation, testing, deployment, observability, and production operations.
- Improve agent performance through evaluations, retrieval improvements, better tools, and production feedback loops.
- Turn production agent learnings into reliable, reviewed software and automation.

## Requirements
- 5+ years of experience building production backend systems, distributed systems, or infrastructure platforms.
- Strong systems design skills and experience owning significant systems from design through production.
- Depth in at least one of: AI agent systems, orchestration, tool use, evaluation, grounding, knowledge graphs, graph data modeling, search, retrieval, ranking, RAG, or semantic search systems.
- Strong backend engineering experience, including API design, service boundaries, data modeling, and complex-system integrations.
- Experience with Kubernetes, GitOps such as ArgoCD, infrastructure-as-code, and cloud platforms.
- Comfort working with Go, TypeScript, Python, or Rust.

## Nice-to-haves
- GPU infrastructure, datacenters, bare-metal systems, hardware failure modes, BMC/IPMI, or cluster schedulers.
- Graph databases.
- Event-driven systems and messaging platforms such as NATS or Kafka.
- Observability platforms such as Prometheus and Grafana.
- Building evaluation frameworks or improving the quality and reliability of LLM-powered systems.

## Compensation and Benefits
- Compensation and benefits details were not provided.

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