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Technologies & tools

Must have

Nice to have

MCP

We are looking for a professional who can own 1–2 projects end-to-end, partnering with internal SMEs to understand current-state processes and requirements. You will collaborate with Architects during the design phase, contribute to building and scaling solutions, and regularly demonstrate outcomes to business stakeholders. In the absence of the Architect, you will act as the primary technical decision-maker, ensuring strong technical direction and seamless project execution.

Your tasks

Engaging stakeholders and conducting discovery sessions
Defining requirements and identifying AI/GenAI use cases
Designing a scalable solution architecture
Building AI/GenAI systems and components
Scaling solutions for performance and reliability
Deploying and managing production environments
Leading teams and driving end-to-end delivery

Requirements

5–8 years total experience with 2–4 years in GenAI/LLM, 12–24 months in LangGraph, and ownership of systems post-deployment
Strong expertise in LangGraph for multi-agent systems, parallel execution, checkpointing, and HITL (non-negotiable), along with proficiency in LangChain (advanced chains, memory, custom tool integration)
Hands-on experience with AWS AgentCore (production preferred) and AWS Bedrock, with a solid understanding of SQL, NL-to-SQL, and LLM-powered data access (Snowflake is a plus)
Experience in systems integration using REST APIs, MCP awareness, and enterprise connectors, along with advanced RAG (hybrid search, re-ranking, query reformulation, retrieval evaluation)
Familiarity with RAG evaluation frameworks (RAGAS, TruLens), automated regression pipelines, and observability tools like LangSmith or LangFuse
Expert-level Python (design patterns, async, testing, CI/CD) with multi-model experience (OpenAI, Claude, Gemini, Llama) and production trade-offs
Good understanding of pro-code vs low-code tools (Copilot Studio, Power Automate), AI dev tools (GitHub Copilot, Cursor, Claude Code, Cline)
Strong stakeholder communication skills
Fluent English required

Nice to have

Hands-on work with AWS AgentCore, including advanced knowledge of its services
Proven delivery of production-grade implementations using MCP / A2A
Familiarity with Google Agentspace or Azure AI Foundry platforms
Background in Document Intelligence solutions (OCR, layout-aware chunking)
Practical use of model fine-tuning techniques (LoRA, QLoRA)
AWS ML, Azure AI, or GCP ML certifications

Job no. 260506-XEOGE

Sii ensures that all hiring decisions are made solely on the basis of qualifications and competence. We are committed to equal and fair treatment of all, regardless of legally protected characteristics. At Sii, we promote a diverse and inclusive work environment, in full compliance with applicable anti-discrimination laws.

Technologie i narzędzia

Wymagane

langgraph LangChain

Mile widziane

MCP

Poszukujemy profesjonalisty, który może prowadzić 1-2 projekty od początku do końca, współpracując z wewnętrznymi MŚP w celu zrozumienia aktualnych procesów i wymagań. Będziesz współpracować z Architektami w fazie projektowania, przyczyniać się do budowania i skalowania rozwiązań oraz regularnie prezentować wyniki interesariuszom biznesowym. W przypadku nieobecności architekta będziesz działać jako główny techniczny decydent, zapewniając silny kierunek techniczny i płynną realizację projektu.

Twoje zadania

Angażowanie interesariuszy i prowadzenie sesji odkrywczych
Definiowanie wymagań i identyfikowanie przypadków użycia AI/GenAI
Projektowanie skalowalnej architektury rozwiązań
Tworzenie systemów i komponentów AI/GenAI
Skalowanie rozwiązań pod kątem wydajności i niezawodności
Wdrażanie i zarządzanie środowiskami produkcyjnymi
Kierowanie zespołami i prowadzenie kompleksowej dostawy

Wymagania

5-8 lat doświadczenia, w tym 2-4 lata w GenAI/LLM, 12-24 miesiące w LangGraph i odpowiedzialność za systemy po ich wdrożeniu.
Silne doświadczenie w LangGraph dla systemów wieloagentowych, równoległego wykonywania, checkpointingu i HITL (nie podlega negocjacjom), wraz z biegłością w LangChain (zaawansowane łańcuchy, pamięć, integracja niestandardowych narzędzi)
Praktyczne doświadczenie z AWS AgentCore (preferowana produkcja) i AWS Bedrock, z solidnym zrozumieniem SQL, NL-to-SQL i dostępu do danych opartego na LLM (Snowflake jest plusem)
Doświadczenie w integracji systemów przy użyciu interfejsów API REST, świadomości MCP i konektorów korporacyjnych, wraz z zaawansowanym RAG (wyszukiwanie hybrydowe, zmiana rankingu, przeformułowanie zapytań, ocena wyszukiwania).
Znajomość frameworków oceny RAG (RAGAS, TruLens), zautomatyzowanych pipeline'ów regresji i narzędzi obserwowalności, takich jak LangSmith lub LangFuse.
znajomość języka Python na poziomie eksperckim (wzorce projektowe, asynchroniczność, testowanie, CI/CD) z doświadczeniem w pracy z wieloma modelami (OpenAI, Claude, Gemini, Llama) i kompromisami produkcyjnymi
Dobre zrozumienie narzędzi pro-code vs low-code (Copilot Studio, Power Automate), narzędzi programistycznych AI (GitHub Copilot, Cursor, Claude Code, Cline)
Silne umiejętności komunikacji z interesariuszami
Wymagana płynna znajomość języka angielskiego

Mile widziane

Praktyczna praca z AWS AgentCore, w tym zaawansowana znajomość jego usług
Udokumentowane dostarczanie wdrożeń klasy produkcyjnej przy użyciu MCP / A2A
Znajomość platform Google Agentspace lub Azure AI Foundry
Doświadczenie w rozwiązaniach Document Intelligence (OCR, layout-aware chunking)
Praktyczne wykorzystanie technik dostrajania modeli (LoRA, QLoRA)
Certyfikaty AWS ML, Azure AI lub GCP ML

Nr oferty 260506-XEOGE

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