Senior / Staff Software AI Test Engineer, AI Engineering

TWG Global AI

$190K — $250K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-7 years in software engineering with focus on test automation
  • Expert in Python with design and library creation experience
  • Hands-on experience in Java for testing services
  • Familiarity with LangGraph or Vercel frameworks
  • Experience in building eval sets for LLM models
  • Testing experience on iOS, plugins, and Chrome extensions
  • Proficient in automated test suite creation with frameworks like pytest and Selenium
  • Experience with CI/CD integrations like GitHub Actions or Jenkins
  • Strong data manipulation skills including SQL

Responsibilities

  • Design scalable test automation frameworks for AI and LLM applications
  • Write maintainable Python for test harnesses and internal tools
  • Build evaluation infrastructure to benchmark agent performance
  • Run performance and load tests for streaming and async systems
  • Integrate tests into the CI/CD pipeline for model validation
  • Implement human-in-the-loop workflows for quality validation
  • Champion quality engineering practices across the team

Benefits

  • On-site position in Santa Monica, CA
  • Bonus in addition to base pay
  • Comprehensive medical benefits
  • Financial benefits and support
  • Additional undisclosed perks
Full Job Description
The Role

TWG Global is seeking a Senior or Staff AI Software Engineer in Test to join our AI Engineering team building commercial-grade AI products. This is a software engineering role focused on test automation. You won't just write test cases, you'll design and build the frameworks, harnesses, evaluation infrastructure, and tooling that make testing AI agents and LLM-powered applications possible at scale.

Our agents are written in LangGraph and run on Azure on the TWG side, with a parallel Vercel-based stack on the Palantir side. You'll write eval sets against both, and you'll validate the surfaces our users actually touch: iOS apps, plugins, and Chrome extensions, not just the model layer.

You'll work shoulder-to-shoulder with AI engineers and data scientists, contributing production-quality code to shared repositories. The ideal candidate is a strong coder, fluent in Python and Java - who has shipped automated test infrastructure in a production environment and has hands-on experience evaluating LLM and agentic systems.

Key Responsibilities

Framework and harness engineering
  • Design and build scalable, reusable test automation frameworks for AI agents, LLM-powered applications, and underlying APIs.
  • Write clean, maintainable Python for test harnesses, eval pipelines, synthetic data generation utilities, and internal tooling.
  • Treat test code as production code: code review, type hints, documentation, library design.

Evaluation infrastructure
  • Build evaluation infrastructure for benchmarking agent performance against SOTA LLMs, competitors, and internal baselines.
  • Own regression suites, golden datasets, rubric-based evals, and metric dashboards.
  • Build tooling for synthetic test data generation, edge-case discovery, and adversarial testing.

Resilience and load
  • Design and run release, system, performance, and load tests against streaming, stateful, and async systems.
  • Build chaos and fault injection tooling for token expiry, connection pool exhaustion, provider failover, and cache pressure scenarios.
  • Drive contract testing across LLM providers (Bedrock, Anthropic, OpenAI) to catch parity drift.

CI/CD and observability
  • Integrate automated tests into CI/CD so every model, prompt, and code change is validated before it ships.
  • Build trace-based assertions on LangGraph state, tool calls, and agent decisions - debugging an agent failure means replaying graph state, not re-running a prompt.
  • Make observability a first-class testing surface (LangSmith, audit logs).

Human-in-the-loop and partnership
  • Implement HIL review workflows where automation alone cannot validate quality, then push the automation boundary outward.
  • Partner with AI engineers and data scientists on model evaluation, training and eval data prep, and root-cause debugging of complex end-to-end failures.
  • Champion quality engineering practices across the team: code review, coverage standards, observability, reproducibility.
  • Ensure user-centric validation so AI outputs are accurate, reliable, and meet real-world application needs.

Requirements
  • 3-7 years of software engineering experience, with a meaningful portion focused on test automation, SDET, or software engineering in test roles.
  • Expert-level Python. You write Python every day, design libraries other engineers use, and apply OOP and clean-code practices.
  • Hands-on Java experience, enough to read, write, and test Java services, not just touch them.
  • Working understanding of the LangGraph or Vercel frameworks: graph state, nodes, edges, tool calls, and how to write evals against agentic flows.
  • Demonstrated experience building eval sets for LLM models (this is critical to the role).
  • Experience testing across multiple client surfaces: iOS apps, plugins, and Chrome extensions.
  • Hands-on experience building automated test suites with frameworks such as pytest, Selenium, Playwright, Cypress, or similar.
  • Proven experience integrating test automation into CI/CD systems (GitHub Actions, Jenkins, CircleCI, GitLab CI, or similar).
  • Strong skills in data manipulation, test data preparation, and SQL.
  • Bachelor's degree or higher in Computer Science, Engineering, or a related field.

Strongly preferred:
  • Experience with Azure (our primary cloud) and containerization (Docker).
  • Experience testing RAG pipelines, agentic workflows, or multi-step tool-calling systems.

Benefits

Position Location:

This position is located in Santa Monica, CA (on-site).

Compensation:

The base pay for this position is $190,000-250,000. A bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits.

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