
Job Overview
Location
New York City Office
Job Type
Full-time
Category
Software Engineering
Date Posted
April 7, 2026
Full Job Description
đź“‹ Description
- • The Forward-Deployed Engineer (FDE) at Tessera Labs is a hybrid technical and customer-facing role focused on end-to-end project delivery and long-term customer success for enterprise AI implementations. You will be staffed on the company’s biggest projects, partnering with strategic clients to take ownership of implementations from initial data discovery through final production rollout, ensuring sustained business value through production-ready multi-agent AI solutions.
- • Day to day, you will lead technical deep-dive sessions with clients to map complex data landscapes and business processes to AI workflows; build, deploy, and maintain custom multi-agent AI systems using Python and Tessera’s tools; analyze, clean, and transform customer data for live AI workflows; serve as the primary technical liaison translating technical concepts into business outcomes for stakeholders; and gather insights from client engagements to inform product and engineering roadmap decisions.
- • Tessera Labs is redefining enterprise AI adoption by building multi-agent AI systems that automate complex workflows across platforms like SAP, Salesforce, Workday, Snowflake, and MuleSoft. Backed by Foundation Capital and led by a world-class founding team, the company moves fast with extreme ownership to bring real AI automation to enterprises with speed, precision, and measurable impact.
- • In this role, you will develop deep expertise in enterprise AI implementation, strengthen your ability to bridge technical and business domains, gain hands-on experience with complex data migrations and system integrations, and grow into a trusted technical advisor for Fortune 500 clients—positioning yourself at the forefront of applied AI transformation.
Skills & Technologies
About Tessera Labs, Inc.
Tessera Labs provides a secure platform for developers to integrate, evaluate, and deploy large language models. Its APIs and control layer streamline access to multiple models while enforcing policy, monitoring usage, and protecting sensitive data across applications. The company focuses on governance, observability, and compliance tooling that lets enterprises adopt generative AI safely at scale.
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