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.
Benefits For You
Diverse portfolio of clients
Wide portfolio of technologies
Employment stability
Remote work opportunities
Contracts with the biggest brands
Great Place to Work Europe
Many experts you can learn from
Open and accessible management team
