GenAI / ML Architect

Experis to światowy lider rekrutacji specjalistów i kadry zarządzającej w kluczowych obszarach IT. Z nami znajdziesz konkurencyjne oferty zatrudnienia oraz ciekawe projekty IT skierowane zarówno do ekspertów z wieloletnim doświadczeniem, jak i osób, które dopiero zaczynają swoją przygodę w branży IT.

• 10+ years in software architecture, software development, data engineering, or ML engineering, with deep hands-on GenAI / agentic AI expertise
• Proven track record designing and delivering autonomous multi-agent systems at enterprise scale
• Expert-level understanding of agentic architecture patterns — able to set technical direction for large teams
• Deep knowledge of model orchestration, inference cost optimization, and model selection (commercial and open-source)
• Experience architecting large-scale vector data systems and embedding pipelines
• Ability to design secure, privacy-preserving AI systems resilient to hallucinations and adversarial inputs
• Expert-level cloud architecture experience (AWS, Azure, or GCP)
• Deep LLMOps expertise: model versioning, evaluation pipelines, prompt management, cost monitoring, CI/CD for AI
• Ability to define AI-assisted development tooling standards and best practices for engineering teams
• Exceptional communication skills with engineering teams and C-level stakeholders (Polish and English)

• Define enterprise AI strategy: commercial vs. self-hosted open-source models, optimizing cost, performance, security, and compliance
• Architect large-scale autonomous multi-agent ecosystems: orchestration, task delegation, context management, agent-to-agent communication
• Design the enterprise integration layer connecting agents to corporate systems (REST/API, event-driven, MCP, custom connectors)
• Design distributed vector architectures and knowledge layers: embeddings pipelines, indexing, metadata management, RAG policies
• Own security and compliance at the architecture level: PII handling, authorization, access control, agent quality metrics, AI Act adherence
• Own production excellence: enterprise cloud architecture with full observability, automated evaluation, monitoring, cost governance, Responsible AI guardrails
• Act as technical authority: set architectural standards, coordinate across DevOps/Security/business, mentor senior engineers, shape Accenture's global reference architecture for agentic AI