AI Architect

We are searching for an experienced AI Architect with expertise in AI Agentic solutions to join our client’s growing team. You’ll design state-of-the-art agentic systems using the latest technology available, pushing what’s technically possible today into what a brand’s relationship with its customers could feel like tomorrow - more responsive, more personal, more human. The Senior AI Architect is a hands-on technical authority who owns architecture across multiple client engagements and sets the standards other architects and engineers build against. Your impact extends beyond any single engagement - to the platform, the people, and the business decisions that shape how the practice builds AI.

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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

• Design end-to-end architectures for agentic AI systems: compute, networking, identity, data, model access, observability, evaluation, and cost.
• Set the standards and reference architectures that make each new engagement cheaper, faster, and safer to build - including the platform, CI/CD, evaluation pipelines, and monitoring every agent project runs on.
• Lead security and compliance workstreams with enterprise clients - threat modeling, vendor assessments, and designing for regulations like GDPR and the EU AI Act.
• Sit on the architecture governance board, improving standardization and reuse across the practice.
• Review designs with engineers and unblock them when something is genuinely hard.
• Make build-vs-buy and platform decisions, writing down the reasoning, and design for portability so clients aren’t locked into one provider.

  Stay hands-on enough to build - comfortable in a terminal, able to prototype the patterns you propose.

• Frame technical constraints as business trade-offs, not reasons to say no.
• Partner with Product Managers on the cost-to-serve and margin implications of architectural choices.
• Contribute to the practice’s Center of Excellence for agentic AI, and represent it through internal and external thought leadership (e.g. On The Map sessions).
• Partner with technology vendors on roadmap influence - validating designs and shaping product direction through feature requests.

Required Qualifications

• 6+ years in software engineering, including several years architecting production AI systems - from ML pipelines to modern LLM and agentic architectures, with solid MLOps/LLMOps practice.
• Deep expertise in at least one major cloud (Azure, GCP, or AWS) and working fluency in a second, including networking, identity, security, and cost management.
• A proven record of taking systems through enterprise security and compliance processes.
• Solid grasp of data architecture: pipelines, warehouses/lakehouses, access control, and governance.
• Familiarity with agent frameworks or SDKs (e.g., Claude Agent SDK, LangGraph, ADK) and protocols like MCP and A2A.
• The ability to communicate architecture clearly to both engineers and executives.

Nice-to-Have Skills

• Experience running LLM-based systems in production - model gateways, API management, token cost optimization.
• Exposure to retrieval systems, vector databases, and RAG.
• Understanding of AI-specific risk: prompt injection, data leakage, and agent permission scoping.
• Awareness of the AI regulatory landscape (EU AI Act, sector-specific rules).

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.