AI Engineer

Role: AI Engineer

Location: Athens, Greece (Hybrid: 2 days/week in office, 3 days remote)

Salary: Competitive package on offer

Role Mission:

Own the introduction and scale‑up of AI‑driven development practices inside a legacy but evolving product suite.

What You’ll Do:

AI‑driven engineering

• Design and implement AI‑powered components and features in the existing software platform
• Implement agentic workflows (multi‑step agents that call tools, APIs, and services)
• Stand up and maintain RAG pipelines (chunking, embeddings, retrieval, evaluation)
• Integrate LLMs into workflows where they materially improve developer or user productivity
• Set up and use MCP (Model Context Protocol) or equivalent tool‑calling frameworks so agents can safely and reliably Read/write data, call downstream services, Orchestrate multi‑step tasks

Full‑stack / backend product work

• Ship production features end‑to‑end, with an emphasis on the backend
• Design APIs, data models, and service boundaries
• Implement business logic, persistence and integrations
• Collaborate with frontend engineers (currently Vue 3 / .NET stack; cross‑stack hires welcome if willing to switch stack)
• Work in (and steadily modernize) a brownfield codebase
• Improve existing patterns instead of just replicating legacy designs
• Incrementally refactor towards cleaner, more modular, more testable services

Loop engineering / AI‑first SDLC

• Use AI agents across the full software development lifecycle
• Requirements → design → implementation → tests → documentation
• Treat AI as a set of “junior agents” that you direct
• Run multiple agents in parallel on different sub‑tasks
• Inspect and correct their outputs
• Improve prompts, tools and workflows instead of manually patching generated code
• Help define how the org will do loop engineering over the next 2–3 years
• Establish conventions, patterns, templates and internal examples
• Partner with other engineers and team leads to adopt these practices

Technical seniority

• Be the “been‑there‑done‑that” AI‑engineering reference point inside the team
• Pair with other engineers to show how to build features with agents / RAG / LLMs
• Review designs and PRs with a focus on AI‑assisted development and system quality
• Act as a bridge between
• Existing engineers who know the product/domain deeply.
• Newer approaches (AI, automation, cloud‑style architecture thinking)

Profile of hire - what would make you successful:

• You are a proven software engineer who has shipped production systems
• You already use LLMs aggressively for building software and/or product workflows
• You can explain, with concrete examples:
• How you used agents, RAG, tool‑calling, or similar in real projects
• How you changed the way you work because of AI (not just “I use Copilot for autocomplete”)
• You are comfortable in ambiguous brownfield environments
• You don’t wait for perfect greenfield; you make the current system better
• You think in systems, not just functions
• You can map how data flows, how services interact, where responsibilities should sit
• You instinctively automate
• If you do something manually more than once, you look for a way to script or systematize it.

Required Experience & Skills:

Core engineering

• Strong backend or full‑stack engineering background
• Experience shipping non‑trivial production applications (web / SaaS / enterprise systems or similar)
• Comfortable taking a problem statement (“what”) and defining the “how”
• For this role we are targeting senior‑level engineers, i.e. people who can:
• Resolve ambiguity
• Propose and drive solutions
• Guide others

AI / LLMs

Hands‑on experience in at least several of the following:

• Building or integrating:
• Agentic workflows (multi‑tool, multi‑step agents)
• RAG systems (document ingestion, chunking, embeddings, retrieval, evaluation)
• Tool‑calling / function‑calling integrations
• MCP or analogous frameworks for connecting models to tools and data
• Using LLMs to materially change how you build software
• Letting AI generate substantial portions of code and tests
• Iterating by improving prompts, tools and constraints rather than manually “fixing” all outputs
• Managing multiple AI “assistants” in parallel

Clear understanding of:

• Where AI is genuinely helpful vs. where it’s fragile or inappropriate
• Typical failure modes: hallucinations, prompt brittleness, security/privacy concerns

System thinking & architecture

• Ability to reason about entire systems
• Data flows, latency and failure points
• Integrations between legacy components and new services
• Experience in at least one modern backend stack (e.g. .NET, Java, Node, Python, Go, etc.)
• You must be willing and able to move into our stack (currently .NET + Vue 3; cloud‑style architectures on the roadmap even though many deployments are on‑prem).

Collaboration & communication

• Strong communication skills in English
• Can explain complex technical ideas clearly to other engineers and to non‑technical stakeholders
• Comfort pairing with engineers whose background is mostly “traditional software on‑prem” and helping them see a better way forward
• Ability to give and receive constructive code/design review

Please apply for more information.