Senior Engineer, AI Systems
Indexed description
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
- Senior-level software engineering in Python/Typescript, with production ownership: you have deployed, monitored and been accountable for systems in live use
- You have shipped an LLM or agent system that reached production, was used by people outside your team, and was maintained by you afterwards
- You have a working method for knowing whether a change to a prompt, model or pipeline improved the system
- You have worked under data security or compliance constraints, including limits on what may be sent to third-party model providers, and you understand the failure modes specific to LLM systems - prompt injection, data leakage across tenants, unsafe tool invocation
- Retrieval at scale: hybrid search, reranking, permissioned or fast-changing document sets
- Agent frameworks, MCP
- Bedrock / Vertex / Azure OpenAI
- Asynchronous and long-running systems: queues, idempotency, durable state
- Client-facing consulting
Benefits
- Competitive remuneration package
- Flexible working hours
- Fully remote working policy
- Food and gift vouchers
- Additional health insurance
- Great work-life balance and 25 days annual vacation
- 1 day Birthday vacation
- A positive and fun environment
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