Enterprise AI Architect / Lead AI Solutions Engineer
New
I
ITLTAI, HR consulting
Miejsce pracy/praca zdalna: Zapewniamy pełną (100%) swobodę pracy zdalnej; Country code: PL, Standardowe polskie godziny pracy (przy czym 2-3x w tygodniu późniejszy start i praca max do 19:00)ContractLead
Salary200 - 220 PLN per hour
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Job Details
- Languages
- Angielski na poziomie C1
- Required Skills
- Node.jsTypeScriptAngularNest.jsCI/CDPrompt EngineeringLLM
Requirements
- Operate at Architect, Principal, or Lead level, beyond execution-only work.
- Be hands-on with current code writing and code review.
- Have experience architecting real systems, including modules, integrations, reuse, versioning, and non-functional requirements.
- Have strong engineering fundamentals in a modern technology stack.
- Have practical experience with Git, code review, automated testing, and CI/CD.
- Have hands-on experience with modern AI tools and platforms, and experience delivering LLM systems used by end users rather than prototypes.
- Know agentic patterns including tool use or function calling, MCP, prompt engineering, context engineering, and orchestration.
- Be able to assess when AI is appropriate and when conventional solutions are better.
- Have experience evaluating and improving nondeterministic systems.
- Have client-facing experience with clients and senior business stakeholders, including presales solution shaping, scoping, estimating, and presentation.
- Be able to explain technical solutions and trade-offs to nontechnical audiences.
- Be prepared to own capability architecture, standards, shared components, platform-level decisions, and security and compliance for sensitive HR data.
- Have English proficiency at C1 level.
Responsibilities
- Work directly with senior business stakeholders and domain experts.
- Identify processes suitable for automation and select tools, platforms, and approaches for business problems.
- Prepare and present solution proposals covering scope, approach, effort, and impact; contribute to presales.
- Design, build, test, and maintain reusable AI skills, and write and review production-quality code.
- Build evaluation layers using golden cases, acceptance criteria, and regression checks.
- Debug AI agent behavior and integrate solutions with platforms and data sources.
- Run user pilots and iteratively improve solutions.
- Define and enforce standards for creating, reviewing, versioning, and releasing AI skills.
- Track AI tooling developments and implement appropriate solutions.
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