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.
• Last-Mile Delivery: Build the custom workflows, services, and integrations required for last-mile delivery. This work is deeply technical, and you should be comfortable diving into any layer of the stack including frontend, backend, data pipelines, or infrastructure to execute whatever changes or additions a customer engagement requires.
• 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.
• Customer Communication: Lead technical conversations with enterprise customers, asking the right questions to unlock relevant data sources, shape agent discovery approaches, and drive successful deployment of the agent into their environment. You will help build out their roadmaps based on needs you identify in collaboration with customer counterparties.

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).

Nice to Have

• 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.

Compensation

We offer competitive compensation, startup equity, health insurance, and additional benefits. The U.S. base salary range for this full-time, in-person role in New York is $150,000-$300,000, plus equity and benefits. Our salary ranges are based on location, level, and role. Individual compensation is determined by experience, skills, and job-related knowledge.