Senior Engineer, AI Systems

Tryzens Global is a digital commerce agency that helps the world's most ambitious retailers scale their businesses internationally. We are the only global support partner in digital commerce operating across every time zone, with deep experience solving complex retail integrations around the world. We provide best of breed solutions and services to global businesses within retail, wine & spirits, beauty & cosmetics, automotive, financial services and other industries. We have built our delivery focused reputation upon technical innovation, in-depth business knowledge, and creative vision, all of which supports our objective of helping clients to gain true value from their technology stacks. We have a platform-neutral independent approach working with the world’s leading technology partners like Shopify, Agentforce(Salesforce), SAP & Adobe. We are embedding artificial intelligence across every stage of our delivery lifecycle and are looking to grow our AI Practice in Sofia. We are looking for an experienced , smart and energetic person to join our team of talented professionals as a Senior AI Developer. The AI Developer role is a hands-on engineering role within the Tryzens AI Practice and is focused on building AI-augmented delivery capabilities across our core technology platforms.

Responsibilities ●       Design, build and operate LLM- and agent-based features in production - architecture through deployment, monitoring and iteration - with cost and latency treated as design constraints, not later optimisation ●       Integrate models with our systems and data: APIs, tool calling, multi-step orchestration, retrieval where the task requires grounding in specific data ●       Build the evaluation and observability that make behaviour changes visible before release rather than after: test sets, automated scoring, tracing, per-task cost ●       Design for non-deterministic failure - output validation, fallbacks, degradation paths, human checkpoints where an error cannot be absorbed ●       Work with clients and product owners to turn ambiguous requirements into scoped, testable capabilities, including judging when an LLM is the wrong tool