We are the 1st Hub for Developers! Our motto is “From Developers to Developers”! Our vision is to provide real career opportunities for candidates that want to take the next step in their career. Code.Career is the first process that you will speak with developers (only!) and tech (freak) experts!

Our client is a leader in personalized customer experiences. The company is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper-personalization at scale, marketing automation, and CRM. With the brain of a consultancy, the heart of an agency, and the power of technology and data, they work with some of the world’s most admired brands on their transformation journey to becoming truly customer-centric. Together, they are 1000+ technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

Key Responsibilities

• Designing end-to-end architectures for agentic AI systems: compute, networking, identity, data flows, model access, observability, and cost.
• Leading security and compliance workstreams with enterprise clients — threat modeling agent systems, answering vendor assessments, and designing for regulations like GDPR and the EU AI Act.
• Building and evolving our internal platform: the shared infrastructure, CI/CD, evaluation pipelines, and monitoring that all our agent projects run on.
• Reviewing designs with engineers and unblocking them — you’ll be the technical authority they pull in when something is genuinely hard.
• Making build-vs-buy and platform decisions, and writing them down so the reasoning survives.
• Working hands-on when it matters. This is an architect role, not a slideware role —you should still be comfortable in a terminal, and we expect you to prototype the patterns you propose.
• Mentoring engineers on cloud, security, and architecture fundamentals — raising the whole team’s bar.

Required Qualifications

• 8+ years in software/cloud engineering, including several years architecting production systems for large organizations.
• Deep expertise in at least one major cloud (Azure, GCP, orAWS) and working fluency in a second — including networking, identity (IAM/Entra), security services, and cost management.
• Strong infrastructure-as-code and platform engineering experience (Terraform or similar, Kubernetes, CI/CD, observability stacks).
• A proven record of taking systems through enterprise security, compliance, and procurement processes — you’ve sat in the room with a client’s security team and come out with an approval.
• Solid grasp of data architecture: pipelines, warehouses/lakehouses, access control, and data governance. (Experience with platforms like Snowflake, BigQuery, or Databricks is a plus.)
• The ability to communicate architecture clearly to two very different audiences: engineers who will build it, and executives who will fund it.
• Pragmatism. You know the best architecture is the one that ships, passes review, and can be operated by the team that exists — not the one with the most boxes on the diagram.

Nice-to-Have Skills

• Experience running LLM-based systems in production — model gateways, API management for AI providers, token cost optimization.
• Familiarity with agent frameworks or SDKs (e.g., Claude Agent SDK, LangGraph) and protocols like MCP, and what they imply for infrastructure.
• Exposure to retrieval systems, vector databases, and the data plumbing behind RAG.
• Understanding ofAI-specific risk: prompt injection, data leakage through model providers, agent permission scoping, and how to design controls for them.
• Awareness of the AI regulatory landscape (EU AI Act, sector-specific rules) and what it means for system design.
  Bonus: you’ve already taken an AI or ML system through an enterprise security review — or built the platform other teams’ AI projects run on.

What They Offer

• Own the architecture for one of the most interesting workload types in the industry right now — for global clients like Coca-Cola, IKEA, Volvo, and DELL.
• Shape the playbook, don’t inherit it. The patterns for enterprise agentic AI are being written now, and you’ll be writing theirs.
• Work with a team of strong engineers who move fast — your job is to make fast also safe, not to slow things down.
• Be part of a well-established global hub in Athens, with international exposure and career opportunities across their offices around the world.