Location: San Jose, CA or New York City
Remote: Considered; travel required
About Tessera Labs
Tessera Labs is redefining how enterprises adopt and operationalize Artificial Intelligence. Backed by Foundation Capital and led by a world-class founding team, we build governed, multi-agent AI systems that automate complex business workflows across enterprise platforms such as SAP, Salesforce, Workday, Snowflake, MuleSoft, and more.
Our mission is to bring real AI automation to the enterprise — with speed, precision, and measurable impact. We move fast, operate with extreme ownership, and build at the frontier of applied AI for large-scale enterprise transformation.
Role Summary
The Senior Forward-Deployed Engineering Lead (Senior FDE) is a senior, hands-on technical leader embedded within a delivery pod at customer sites, led by a Technical Project Manager (TPM). The Senior FDE is responsible for leading the Forward-Deployed Engineers (FDEs) within the pod and owning the technical execution and quality of customer-facing AI modernization work.
With 8+ years of experience, the Senior FDE acts as the primary technical authority for forward-deployed execution at client sites, while partnering closely with the TPM, Systems Engineers and Solution Architects. This role is accountable for technical correctness, architectural integrity, and execution excellence throughout the engagement.
The Senior FDE must have led at least two complex projects end-to-end as a technical lead, including one AI/ML-driven project.
Key Responsibilities
Technical Leadership Within the Pod
Serve as the technical lead for FDEs within a TPM-led delivery pod.
Provide day-to-day technical direction, task guidance, and execution oversight for the FDE team.
Review and validate designs, implementations, and code to ensure quality, scalability, and maintainability.
Act as the primary technical escalation point for complex or high-risk issues within the pod.
Partnership with the Technical Project Manager
Work closely with the TPM, who owns pod leadership and delivery management.
Provide technical input into scope definition, sequencing, estimates, dependencies, and feasibility.
Identify technical risks early and propose mitigation strategies to support predictable delivery.
End-to-End Technical Execution
Lead technical delivery from discovery and architecture through implementation, deployment, and stabilization, within the execution plan defined by the TPM.
Design and implement AI-driven workflows, integrations, and multi-agent architectures under real-world enterprise constraints.
Remain hands-on with coding, debugging, and deployment, particularly for complex or mission-critical components.
Applied AI & Enterprise Engineering
Lead implementation of LLM-based and multi-agent AI systems in enterprise environments.
Integrate AI workflows with enterprise platforms such as SAP ECC/S/4HANA, Salesforce, Workday, Snowflake, MuleSoft, Oracle, and similar systems.
Ensure solutions meet enterprise standards for performance, observability, security, and governance.
Customer-Facing Technical Leadership
Act as the senior technical representative during customer workshops, architecture sessions, and implementation phases.
Lead technical deep dives with customer engineering and IT teams.
Communicate technical decisions, trade-offs, and constraints clearly to both technical and non-technical stakeholders.
Coaching & Execution Excellence
Mentor and develop FDEs through hands-on guidance, code reviews, and design discussions.
Reinforce best practices for forward-deployed execution, documentation, and operational readiness.
Provide structured feedback to Product and Platform teams based on real-world delivery experience.
Technical & Domain Skills
Software Engineering
Advanced proficiency in Python; ability to write, review, and debug production-quality code.
Strong experience with APIs, integrations, and distributed systems.
AI / ML & Agent-Based Systems
Hands-on experience delivering AI-enabled or ML-driven systems in production.
Strong understanding of LLMs, agent orchestration patterns, and AI operational constraints.
Enterprise Systems & Architecture
Experience integrating with enterprise platforms (SAP, Salesforce, Workday, Snowflake, Oracle, etc.).
Familiarity with data harmonization, workflow automation, and legacy system modernization.
Cloud & Infrastructure
Experience deploying and operating systems in cloud environments (AWS, GCP, Azure).
Familiarity with monitoring, logging, and observability best practices.
Required Qualifications
8+ years of experience in technical consulting.
Proven experience leading at least two projects end-to-end as a technical lead, including one AI/ML-driven project.
Experience mentoring or leading engineers in a customer-facing delivery environment.
Strong communication skills and comfort engaging directly with customer technical teams.
Willingness to travel to customer sites as required.
Behavioral Expectations
Strong ownership over technical execution and solution quality.
Effective collaboration with TPMs, Solution Architects, and engineering partners.
Calm, decisive execution in high-pressure customer environments.
Balance speed with engineering rigor and long-term maintainability.
Effective use of AI tools to accelerate development, troubleshooting, and documentation.
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