AI Engineer (GenAI/Agentic Systems)

DCG sp. z o.o. is a recruitment company focused on providing experienced professionals and continuous support to meet business needs. They are currently growing and undertaking numerous recruitment projects for their partners.

• 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms)
• Proven ability to ship production-grade LLM applications (RAG, tool/function calling, agent orchestration) with reliability, security, and observability
• Proficiency in at least one backend language used for AI systems (Python preferred) and comfort integrating with enterprise stacks (C#/.NET is a plus)
• Hands-on experience building and integrating RESTful APIs; GraphQL experience is a plus
• Experience integrating with external services and internal platforms via APIs and event-driven patterns
• Hands-on experience building LLM-powered applications end-to-end: prompt design, tool/function interfaces, structured outputs, and streaming user experiences
• Experience with RAG systems: document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation
• Experience with agentic frameworks and orchestration concepts (planning, routing, tool use, human-in-the-loop interruptions)
• Experience with frameworks such as LangGraph, LangChain, Microsoft Semantic Kernel, or equivalent
• Experience working with model platforms (e.g., Azure OpenAI/OpenAI or similar) and designing for reliability (timeouts, fallbacks, quotas)
• Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights)
• Experience with search and retrieval services (Azure AI Search or similar) and building scalable, network-bound workloads
• Hands-on experience with CI/CD and automated deployments (Azure DevOps preferred), including containerization (Docker)

• Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources
• Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation
• Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs
• Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed
• Partner with other engineers to set direction, mentor, and unblock the team – helping establish strong foundations for the AI initiative
• Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads
• Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation
• Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI