Technical Project Manager at Tessera Labs

Location: San Jose, CA or New York City Remote: Considered; travel required About Tessera Labs Tessera Labs is redefining how enterprises modernize their most complex systems. Backed by Foundation Capital and built by leaders in AI and enterprise transformation, Tessera delivers governed, multi-agent AI built specifically for ERP modernization. Tessera compresses ERP modernization from years to weeks. Our platform accelerates data harmonization, remediates and optimizes legacy code, orchestrates workflows across ERP/CRM/Finance etc. stacks, and safeguards mission-critical operations with audit-ready governance. Our mission: Modernize global enterprises safely, automatically, and at unprecedented speed. We move fast, own outcomes end-to-end, and build at the frontier of applied AI for large-scale transformation. Role Summary The Technical Project Manager (TPM) is the project leader ensuring that Tessera’s multi-agent AI solutions are delivered predictably, safely, and successfully across complex enterprise environments. Unlike a traditional project or program manager, this role requires significant technical depth: - You must understand enterprise system architectures, data flows, integrations, and AI-driven automation. - You must be able to speak fluently with both customer technical teams and Tessera’s AI, data, and engineering teams. - You will provide technical guidance during issue resolution, support architecture discussions, and ensure teams stay aligned on what is required and what is technically feasible. You will also lead delivery pods composed of Forward-Deployed Engineers, Data Engineers, and Solution Architects to execute modernization programs across ERP and connected systems. The ideal candidate has delivered ML programs and Enterprise Systems transformation initiatives and thrives at the intersection of AI, architecture, and enterprise-scale delivery. Key Responsibilities 1. Technical Program Leadership & Delivery - Own end-to-end delivery of multi-agent AI modernization programs across ERP, CRM, various Enterprise systems and connected systems. - Lead a cross-functional delivery pod (Forward-Deployed Engineers, Data Engineers and System Engineers) to drive technical execution and customer outcomes. - Excels at engaging with customers, translating their needs into actionable plans, and ensuring alignment between stakeholders and delivery teams. - Engage deeply in technical discussions about data quality, system landscapes and governance. - Translate ambiguous enterprise requirements into clear, technical scopes, milestones, dependencies, and risk structures. 2. Technical Communication & Cross-System Alignment - Act as the technical bridge between customer engineering teams and Tessera’s AI/product/engineering organizations. - Communicate architectures, technical decisions, constraints, and trade-offs clearly to both technical and non-technical stakeholders. - Facilitate discovery workshops where you interpret complex system landscapes and ensure technical alignment. 3. Execution Management & Process Optimization - Drive Agile workflows with discipline and structure to achieve predictable delivery. - Anticipate technical and operational risks; create clear mitigation plans. - Implement best practices for scaling multi-agent AI delivery across customers. - Track KPIs, delivery velocity, quality metrics, and execution health. 4. Enterprise-Grade Governance & Deployment - Ensure delivery meets enterprise standards for security, compliance, auditability, and change governance. - Oversee technical prerequisites for integration across enterprise systems, e.g. SAP, Salesforce, Workday, Snowflake, and other enterprise platforms. 5. Customer Engagement, Escalation, & Problem Solving - Serve as the primary technical operations contact during onboarding, implementation, and expansion. - Manage customer escalations; coordinate engineering response with clear, timely communication. - Partner closely with customer IT and transformation teams to drive alignment and unblock technical issues. 6. Startup Mindset & Extreme Ownership - Operate in a high-velocity, high-ambiguity environment. - Bring structure, clarity, and momentum to evolving customer needs. - Travel to customer sites for workshops, solution design, and program oversight. Technical & Domain Skills Technical Communication & Architecture Understanding - Ability to read, understand, and explain technical concepts. - Comfort discussing system constraints, API limits, error handling, data models, and logical workflows with engineering teams. Enterprise Systems Expertise - Understanding of ERP/CRM/Enterprise systems (SAP ECC/S/4, Salesforce, Workday, Snowflake, MuleSoft, Oracle etc.). - Familiarity with master data harmonization, code remediation, process orchestration, and legacy modernization. AI / ML & Automation - Experience delivering ML programs or working with ML/AI engineering teams. - Understanding of LLMs, multi-agent AI orchestration, and enterprise automation frameworks. Program & Delivery Management - Strong command of Agile methodologies, Jira workflows, and cross-functional delivery orchestration. - Experience running technical programs with large-scale dependencies. Required Qualifications - 4–6+ years of technical program management or engineering program delivery experience. - Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field. - Proven ability to communicate with engineering teams in technical contexts. - Strong technical literacy and ability to engage in architecture, data, and system integration topics. - Excellent communication skills across technical and business audiences. Preferred Qualifications - Delivered Machine Learning programs and/or Enterprise Systems modernizations. - Background in ERP transformation (SAP strongly preferred), data quality programs, or system integrator environments. - Experience in high-growth startup environments. - PMP, Scrum Master, or SAFe certification. - Experience with LLM/agent-based systems or AI-driven enterprise automation. Behavioral & Problem-Solving Expectations - Balance engineering depth with program structure and executive communication. - Operate with extreme ownership and a bias for clarity and action. - Thrive in ambiguity; create structure where none exists. - Strong stakeholder management across customer executives, engineers, and cross-functional teams. - Adapt quickly, simplify complexity, and drive alignment. - Use AI tools to accelerate planning, documentation, and delivery.