2 months 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.

Tech Stack

Categories

Tessera Labs

About Tessera Labs

1-10 employees

Tessera Labs builds multi-agent AI systems that automate complex enterprise workflows across platforms such as SAP, Salesforce, Workday, Snowflake, and Databricks. It sells AI automation software and services to large organizations seeking to operationalize AI in back-office and data operations. Founded in 2022 and headquartered in London, the privately held company focuses on deploying production AI within existing enterprise stacks.

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