AI Solution Architect / Technical Owner

Nasze wymagania: 5+ years of professional experience in solution architecture, cloud engineering, or senior DevOps/platform engineering roles. Hands-on experience with AWS Bedrock or Azure AI/OpenAI services in a production or PoC context. Strong cloud platform knowledge: AWS (SageMaker, Lambda, S3, ECS/EKS) or Azure (Azure AI Studio, AKS, Azure Functions, Cognitive Services). Practical experience designing and operating Vector Databases for AI workloads (Pinecone, Weaviate, pgvector, Chroma, or Qdrant). Solid DevOps skillset: Infrastructure as Code (Terraform or CDK), CI/CD pipelines, Docker, Kubernetes, and monitoring/observability tooling. Demonstrated experience delivering AI or ML solutions in production — agentic systems, RAG pipelines, LLM integrations, or conversational AI. Strong communication and facilitation skills: able to lead workshops, present architectural proposals, and align both technical and non-technical stakeholders. Prototyping ability — comfortable writing and owning code (Python preferred) to validate architecture decisions quickly. Mile widziane: Experience with agentic AI frameworks: LangChain, LangGraph, CrewAI, AutoGen, or OpenAI Assistants API. Familiarity with MLOps practices: model versioning, experiment tracking (MLflow), and inference pipeline management. AWS or Azure cloud certifications (Solutions Architect, AI/ML Specialty). Experience with fine-tuning or prompt engineering for large language models. Background in regulated industries (finance, insurance, healthcare) where data governance and security are critical. Experience scaling agentic solutions from prototype to production-grade deployment. O projekcie: As an AI Solution Architect / Technical Owner you will take a leading role in designing and prototyping agentic AI solutions for our client. You will join the Sales Companion product team — an agentic AI platform supporting Account Executives and Account Managers in their daily work. The solution follows a hybrid architecture, allowing users to work locally with their own files while leveraging a centralized document library powered by a Vector Database for semantic retrieval. The agent will be cloud-hosted on AWS or Azure using AWS Bedrock with Amazon Q or the Azure AI Foundry equivalent. A working local prototype already exists and will serve as the foundation for further development. You will own the end-to-end technical vision, collaborate closely with the Product Owner and Technical Adoption Specialist, and help shape the emerging engineering team as the product scales toward production readiness. Ways of Working • Comfortable operating as a solo technical lead in early project phases, with the ability to define structure where ambiguity exists. • Proactive and ownership-driven: takes initiative on technical decisions and drives them through to delivery. • Clear and concise communicator across engineering, product, and business stakeholders — able to translate complex AI architecture into understandable terms. • Collaborative mindset with experience working in agile, iterative delivery environments. Zakres obowiązków: Design and own the end-to-end architecture of agentic AI solutions, including agent orchestration, memory, tool use, and multi-agent pipelines. Prototype and validate AI solutions using AWS Bedrock or Azure AI services, driving early-stage technical decisions with working code. Define and implement Vector Database strategies (e.g. Pinecone, Weaviate, pgvector, Qdrant) to support Retrieval-Augmented Generation (RAG) and semantic search use cases. Architect and manage cloud infrastructure on AWS or Azure with a strong DevOps mindset: infrastructure as code, CI/CD pipelines, containerization (Docker/Kubernetes), and deployment automation. Facilitate technical discovery workshops and architecture sessions with client stakeholders; translate business requirements into actionable technical roadmaps. Act as Technical Owner across the delivery lifecycle — guide development teams, conduct architecture reviews, and ensure alignment with architectural standards. Evaluate and recommend LLM frameworks and tooling (e.g. LangChain, LangGraph, CrewAI, AutoGen) appropriate to the project context. Identify and mitigate technical risks early; maintain architectural documentation and decision records. Collaborate with client engineering teams to ensure seamless integration of AI components with existing systems and data pipelines. Oferujemy: Contract under Polish law: B2B or Umowa o Pracę Benefits such as private medical care, group insurance, Multisport card English classes available Hybrid work in Warsaw (Mokotów) or remote possibilites Opportunity to work with excellent professionals High standards of work and focus on quality New technologies in use Continuous learning and growth International team Pinball, PlayStation & much more (on-site)