GenAI / ML Architect
⚲ Warszawa
31 920 - 36 960 PLN netto (B2B)
Wymagania
- GenAI
- Agentic AI
- LLMops
- RAG
Opis stanowiska
Responsibilities:
• 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
Requirements:
• 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)
What we offer:
• 100% remote
• Multisport card
• Private healthcare
• Life insurance
• PowerYou platform – e-learning
• 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
Requirements:
• 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)
What we offer:
• 100% remote
• Multisport card
• Private healthcare
• Life insurance
• PowerYou platform – e-learning
🔍 Dekoder Ogłoszenia
🔴
Define enterprise AI strategy: commercial vs. self-hosted open-source models, optimizing cost, performance, security, and compliance
Oczekuje się, że będziesz podejmować strategiczne decyzje dotyczące wyboru i wdrażania modeli AI, co może wiązać się z presją na minimalizację kosztów i maksymalizację wydajności.
🔴
Architect large-scale autonomous multi-agent ecosystems: orchestration, task delegation, context management, agent-to-agent communication
Projektowanie i wdrażanie złożonych systemów agentowych na dużą skalę, co może oznaczać pracę nad nowatorskimi, ale potencjalnie niestabilnymi rozwiązaniami.
🔴
Own security and compliance at the architecture level: PII handling, authorization, access control, agent quality metrics, AI Act adherence
Będziesz odpowiedzialny za zapewnienie zgodności z przepisami i bezpieczeństwa danych, co może oznaczać dużą odpowiedzialność i konieczność ścisłego przestrzegania procedur.
🔴
Act as technical authority: set architectural standards, coordinate across DevOps/Security/business, mentor senior engineers, shape Accenture's global reference architecture for agentic AI
Oczekuje się od Ciebie przywództwa technicznego i wpływu na globalne standardy, co może oznaczać dużą presję i konieczność zarządzania oczekiwaniami różnych interesariuszy.
🔴
Proven track record designing and delivering autonomous multi-agent systems at enterprise scale
Poszukiwane jest doświadczenie w projektowaniu i wdrażaniu systemów, które mogą być jeszcze w fazie rozwoju i nie mieć ugruntowanej pozycji na rynku.