AI Infrastructure Engineer – Tooling

🔥 1 minute ago

🇺🇸 United States – Remote

💵 $200k - $230k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 20%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Tessera Labs

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

Artificial Intelligence • Enterprise • SaaS

Tessera Labs is a vendor-agnostic, multi-agent AI systems integration platform that gives enterprises a single, unified view across their IT architecture. Pre-trained on thousands of enterprise landscapes and hundreds of years of business process expertise, Tessera adapts to each customer environment to harmonize systems and data and to enable secure, governed execution across ERP and other critical systems. The company emphasizes enterprise-grade governance and controls for regulated industries, accelerating time-to-value while evolving with new data and workflows, and is built on published AI research and patented technology.

📋 Description

• Design, build, and own tooling and services that take AI agents from development to production in customer clouds • Build and maintain internal CLIs, SDKs, and services in Python or Go • Deploy, scale, and tune LLM inference using vLLM and similar serving stacks • Build infrastructure for multi-agent systems, including agent runtimes, tool and connector execution, sandboxing, state management, and safe agent-version rollouts • Own MLOps workflows covering model and prompt versioning, evaluation pipelines, artifact registries, and staging-to-production promotion • Write Kubernetes operators and custom controllers that manage AI workloads • Design, build, and operate production-grade AI agent infrastructure using Kubernetes and Terraform • Support portable infrastructure across Azure, Oracle Cloud, GCP, and AWS, with primary ownership of at least one cloud variant • Improve observability for agent and LLM calls, token and GPU utilization, latency, error rates, and cost • Strengthen security and reliability for workloads in customer environments under strict compliance constraints • Design and own CI/CD for infrastructure, services, and model/agent releases using GitOps and pipeline-as-code • Build self-service tooling for environment provisioning, secret rotation, dependency updates, compliance checks, and release management • Partner with AI, product, and platform engineers to unblock delivery

🎯 Requirements

• 5+ years of experience in infrastructure, platform, or backend engineering (7+ years for senior) • Strong software engineering in Python or Go, with experience building and shipping tools, CLIs, or services used by other engineers • Hands-on experience running LLM workloads in production, including vLLM or a comparable serving stack (TGI, Triton, SGLang, Ray Serve) • Experience building infrastructure for AI agents or LLM applications, including orchestration, tool calling, evaluation, or agent runtimes • Practical MLOps experience: model/prompt versioning, evaluation and release pipelines, and ML observability • Strong hands-on experience with Kubernetes, including writing or extending operators/controllers using Kubebuilder, Operator SDK, controller-runtime, or Kopf • Strong hands-on experience with Terraform and at least one of Azure, Oracle Cloud, GCP, or AWS • Proven experience designing and owning CI/CD systems, GitOps-driven deployments, and release automation • Solid networking fundamentals • Proven experience deploying and operating production systems • GPU infrastructure experience, NVIDIA GPU Operator, MIG, KServe, or Karpenter-style autoscaling for inference is nice to have • Familiarity with LangGraph, Model Context Protocol, OpenAI Agents SDK, or similar is nice to have • Familiarity with OpenTelemetry, Langfuse, or Arize is nice to have • Experience with FluxCD, ArgoCD, or other GitOps controllers is nice to have • Cloud security and DevSecOps experience is nice to have • Deep networking expertise is nice to have • Open-source contributions to AI infrastructure or Kubernetes ecosystem projects are nice to have

🏖️ Benefits

• Equity • Work on cutting-edge AI infrastructure with real enterprise impact • Ownership of foundational systems at an early-stage, high-growth company • Collaboration with a sharp, execution-focused founding team • Opportunity to shape how AI agents are deployed across enterprise platforms

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