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Forward Deployed Engineer

External
Traversal logoTraversal · NY
$150K–$300K/yrFull-timeOn-site3d ago
DatadogKubernetesLLMsMoveObservabilityPandas
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About the role

As a Forward Deployed Engineer at Traversal, you will own the last-mile delivery of the Traversal product by deploying frontier LLMs in production, optimizing multi-step reasoning workflows, and improving the performance and accuracy of our agentic systems. You will be responsible for the end-to-end deployment of the agent into the largest enterprises and ensuring it delivers accurate and actionable insights. This is a highly technical role at the intersection of AI, systems engineering, and customer impact. You'll work across teams to ensure our AI agents interact seamlessly with large volumes of observability data and scale reliably across environments. The insights you generate through your customer-driven work will directly impact roadmaps for all other engineering teams at the company.

Responsibilities

  • AI Agent Architecture: Design and build multi-step reasoning workflows that use LLMs and other components to analyze large-scale observability data.
  • Prompting & Tooling: Develop tooling for prompt engineering, function calling, and agentic orchestration that optimizes latency, reliability, and performance.
  • Production Deployment: Own technical delivery across multiple deployments from first prototype to robust, scalable production environments with low latency and high uptime requirements.
  • Engineering Strategy: Work closely with Platform, Infra, Product, and GTM teams to ensure our AI agents are well-integrated into the broader system and are delivering customer value.

Requirements

  • 3+ years of software engineering experience.
  • Strong Python skills, including experience with Asyncio and Pandas.
  • Strong communicator who is comfortable translating technical details into clear, actionable insights for both engineering and customer stakeholders.
  • Experience building and deploying distributed systems and/or large-scale data processing pipelines.
  • Familiarity with LLMs, prompt engineering, or agentic frameworks.
  • Proven ability to deliver projects end-to-end: from experimentation to production deployment.
  • Strong debugging skills and ability to work across layers (data, infra, model, and application).
  • Experience with observability data and production infrastructure (logs, metrics, traces).
  • Background in AI agent research or open-source contributions to agent frameworks.
  • Experience working with Terraform, Kubernetes, or ML orchestration platforms.

Benefits

Why You Should Join UsWe'll make sure you're fully supported with health insurance, a great tech setup, flexible time off, and plenty of in-office snacks. We offer competitive salary and equity packages, and take thoughtful consideration with every hire on our small, high-impact team.Traversal is fully in-office, 5 days a week, based in New York near Madison Square Park. We have a collaborative, hard-working culture and are energized by building the future of AI-powered software maintenance.Working here means owning meaningful parts of the product, having the flexibility to move fHealth insuranceFlexible scheduleEquity / stock options

Additional Information

About Traversal Traversal is the AI Site Reliability Engineer (SRE) for the enterprise-already trusted by some of the largest companies in the world to troubleshoot, remediate, and even prevent the most complex production incidents. Our mission is to free engineers from endless firefighting and enable them to focus on creative, high-impact work. Our roots remain deeply embedded in AI research, and we're channeling that scientific rigor and creativity into building the premier AI agent lab for the enterprise. Hence, what we're proudest of is assembling the most talented yet nicest group of individuals, including researchers from MIT, Harvard, and Berkeley, to world-class engineers from industry: Citadel Securities, Cockroach Labs, Datadog, DE Shaw, ServiceNow, Glean, Perplexity, Pinecone, and more, to take on one of the hardest problems for AI to solve. Without the entire team, none of this would be possible.


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