3 hours ago
San Jose, CA, USA or New York, NY, USAMid Level

Base Salary

$200k - $250k/yr

Responsibilities

  • Design and ship production agents that understand enterprise landscapes, plan and execute transformations, and prove correctness.
  • Build typed, permissioned, documented tool interfaces for agents operating across enterprise systems.
  • Improve agents through prompting, context construction, tool-use strategy, and decision logic.
  • Build retrieval systems using chunking, indexing, hybrid search, reranking, grounding, and evaluation.
  • Manage large context windows by deciding what to retain, compress, or drop during long agent runs.
  • Apply supervised ML to routing, ranking, classification, anomaly detection, and confidence estimation when appropriate.
  • Build evaluation, regression, monitoring, tracing, alerting, approval, guardrail, and rollback systems.
  • Diagnose production failures from execution traces to root cause and turn customer-specific solutions into reusable platform capabilities.

Requirements

  • 3+ years of experience building and operating production software, including meaningful recent experience with LLM-powered systems.
  • Experience shipping agentic systems used by real users and owning incidents when they failed.
  • Fluency with tool calling, orchestration, context engineering, retrieval-augmented generation, evaluations, and tracing.
  • Experience building and measuring retrieval systems over messy real-world corpora.
  • Background in traditional ML, including supervised learning, feature engineering, and model evaluation.
  • Strong Python skills and comfort with TypeScript.
  • Strong systems thinking, customer-outcome orientation, and ability to build reliably with non-deterministic systems.
  • Preferred experience with enterprise platforms and APIs including SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft, and ServiceNow.
  • Preferred experience with knowledge graphs, ontologies, semantic models, code analysis, program transformation, or automated refactoring.
  • Preferred experience with MCP, sub-agents, agent skill or plugin architectures, distributed systems, or workflow engines.
  • Preferred familiarity with SSO, RBAC, segregation of duties, PII handling, SOC 2, and data residency.
Tessera Labs

About Tessera Labs

51-200 employees

Enterprise transformations shouldn't take years or cost fortunes. At Tessera, we've built a multi-agent AI platform that cuts ERP transformation timelines from years to weeks and reduces costs by more than half—while delivering first-time-right outcomes with enterprise-grade security and governance. We combine the dependability of a trusted integrator with the speed of an AI innovator. Our vendor-agnostic platform is pre-trained on thousands of enterprise landscapes and hundreds of years of expertise, so it adapts to your environment from day one—harmonizing systems and data to deliver secure, governed execution across ERP and other critical systems. Unlike traditional system integrators, ERP vendor tools, AI point solutions, or in-house builds, Tessera delivers transformations that compress timelines by 90%, replace people-heavy manual work with intelligent automation, ensure systems and data harmonize correctly from the start, and avoid vendor lock-in through adaptive intelligence that evolves with your workflows. Tessera creates lasting change in how your processes and systems operate together. As the platform adapts to your environment and evolves with new data, you gain the confidence to modernize with less risk—freeing up resources to reinvest in growth rather than maintaining legacy complexity. Proven in regulated industries. Built for enterprise reality. Reshaping how organizations transform.