GenAI Architect (AI&Data)

The Work

As a GenAI Architect, you will define how autonomous agentic AI ecosystems are designed, built, and governed at enterprise scale—systems where hundreds of specialized agents collaborate to solve real business problems.

You will:

• Define enterprise AI strategy, deciding when to use commercial versus self-hosted open-source models and optimizing for cost, performance, security, and compliance.
• Architect large-scale autonomous multi-agent ecosystems, including agent orchestration, task delegation, context management, and agent-to-agent communication patterns.
• Design the enterprise integration layer connecting autonomous agents to corporate systems through REST/API, event-driven architectures, MCP, and custom connectors.
• Design distributed vector architectures and knowledge layers, including embedding pipelines, indexing strategies, metadata management, and RAG policies.
• Own architecture-level security, compliance, and quality, including PII handling, authorization, access control, factuality, hallucination rate, latency, cost per query, and AI Act adherence.
• Own production excellence across AWS, Azure, or GCP, including observability, automated evaluation pipelines, monitoring, cost governance, and Responsible AI guardrails.
• Act as a technical authority by setting architectural standards, coordinating with DevOps, Security, and business stakeholders, mentoring senior engineers, and shaping global reference architecture for agentic AI.

Interview Note

During the meeting with Technical Partners, be ready to approach complex architectural challenges in practice using your preferred development environment, including AI-assisted tools. Share your screen and walk through your thinking.

What’s in It for You?

• Direct impact on global reference architecture for agentic AI and the design and governance of enterprise-scale autonomous systems.
• Visibility across global projects and C-level stakeholders as a thought leader in enterprise AI.
• Work on cutting-edge AI challenges at enterprise scale.

Here’s What You’ll Need

• Extensive experience (10+ years) in software architecture, data engineering, or ML engineering, with deep hands-on expertise in GenAI and agentic AI.
• Proven track record of designing and delivering autonomous multi-agent systems at enterprise scale in commercial environments.
• Expert understanding of agentic architecture patterns, including defining strategy, evaluating trade-offs, and setting technical direction for large teams.
• Deep knowledge of model orchestration, inference-cost optimization, and selecting commercial and open-source models for each use case.
• Experience architecting large-scale vector data systems and embedding pipelines.
• Ability to design highly secure, privacy-preserving AI systems resilient to hallucinations and adversarial inputs.
• Expert knowledge of AI-assisted development tools and workflows, such as Cursor, Copilot, or similar, including the ability to define tooling standards, best practices, and productive engineering-team setups.
• Deep understanding of LLMOps: model versioning, evaluation pipelines, prompt management, cost monitoring, and CI/CD for AI applications; ability to define LLMOps strategy and ensure production-grade operational maturity.
• Strong cloud architecture experience with AWS, Azure, or GCP.
• Exceptional communication skills for leading technical conversations with engineering teams and C-level stakeholders in Polish and English.

Bonus Points If You Have

• Experience establishing global AI-governance frameworks aligned with regulatory standards, such as the AI Act.
• Experience designing observability layers for enterprise agentic architectures.
• Contributions to open-source projects, published research, or recognized thought leadership in agentic AI.
• Experience scaling engineering teams and establishing technical standards across multiple projects or geographies.

What We Offer

• Permanent employment contract.
• Individual support of a People Lead and a defined professional-development path, including the possibility of a session with a Coach.
• Comprehensive training package: soft-skills, technical and language training, access to e-learning platforms, Gallup test, GenAI training, and possible co-financing of courses and certifications.
• Employee Assistance Program with legal, financial, and psychological consultations.
• Employee Share Purchase Plan with eligibility for quarterly dividends for employee shareholders.
• Paid employee-referral program.
• Private medical care and life insurance.
• Access to the Worksmile benefits platform, including the Multisport card.