AI Agent Developer
Ish ta'rifi
We are partnering with a pioneering industry leader in the gaming and systems development sector. Our Customer designs and delivers premium game content, award-winning systems, and state-of-the-art gaming hardware, providing world-class gaming experiences globally. The project involves working across a distributed portfolio of applications, focusing on implementing quality engineering best practices, improving QA efficiency, and extending automated test coverage.
The Role:
We are seeking an AI Agent Developer to engineer intelligent, LLM-powered agents integrated directly with our core test automation framework. In this role, you will build production-grade agent services that hook into the Java core automation engine, enabling autonomous test generation, execution, and maintenance across our Customer's gaming portfolio to empower QA Automation teams.
Key Responsibilities:
- Agent Architecture & Engineering: Develop and deploy production LLM-powered services in Python using multi-turn agent loops, structured outputs, and tool integration.
- Tooling & Protocol Integration: Design robust tool-server integrations (MCP or similar) connecting AI agents with the underlying Java core framework and device infrastructure.
- Code Context Retrieval: Build repository indexing and code search mechanisms to optimize context feeding for LLM models during test generation and execution.
- Evaluation, Safety & Observability: Establish continuous evaluation suites, model regression detection, safety guardrails, token tracking, and agent run tracing.
- AI Application Engineering: Strong experience delivering LLM-powered features to production rather than to prototype, covering tool use, multi-turn agent loops, structured output, and management of context, latency and cost. Can ship agents as services with authentication, queues and persistent state.
- Evaluation & Quality: Expertise building evaluation sets and regression suites that detect when a prompt or model change has degraded results with a clear metrics proving that.
- Programming Languages: Proven expertise in Python.
- Code Context & Retrieval: Strong experience getting relevant source code in front of a model through repository indexing and symbol or structural search, with the possibility to recognise where embeddings are not the right instrument.
- Tooling & Integration: Experience with Model Context Protocol (MCP) or comparable tool-server design, including tool granularity and returning errors to the model in a form it can act on.
- Safety & Guardrails: Solid understanding of permission boundaries, dry-run modes and human review gates for agents that modify repositories and drive physical devices.
- Agent Observability: Familiarity with tracing agent runs, tracking token spend per feature.
- Cross-language Reading: Ability to read Java and C# well enough to reason about a JVM automation engine and the Unity clients it drives.
- Test Automation Understanding: Solid understanding of what makes an automated test flaky (timing, ordering, state leakage, genuine product defects) and of why a passing test is not evidence that a defect was fixed.
- Domain & Industry Experience: Experience working within a game development environment or the mobile gaming industry, or with Unity.
- Projects for such clients as PayPal, Wargaming, Xerox, Philips, adidas and Toyota
- Competitive compensation that depends on your qualification and skills
- Career development system with clear skill qualifications
- Flexible working hours aligned to your schedule
- Options to work remotely
- Corporate medical insurance covering services of private and public medical centers
- English courses online
- Corporate parties and events for employees and their children
- Gym membership compensation, corporate sport competitions (cybersport included)
- 5 days of paid sick leave per year with no obligation to submit a sick-leave certificate
Ключевые навыки
- Python
- Model Context Protocol
- LLM
- Английский — B2 — Средне-продвинутый
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