Senior Artificial Intelligence/Machine Learning Engineer

Senior Artificial Intelligence/Machine Learning Engineer

Ciklum

Remote, Poland

About the role:

As a Senior Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.

We are looking for an experienced AI Consultant to take over the lead role on a running engagement with a global FMCG/consumer health client. The project delivers a multi-agent GenAI system that ideates and validates new product concepts for the client's R&D organization, drawing on product, consumer, and production data (~74k ingested knowledge chunks across a factual SQL plane and a semantic vector plane).

The system is in active PoC delivery with a defined go-live plan, an evaluation framework (golden-question benchmark + SME-mimicking judge panel), and a pilot with the client's Product Research team scheduled for late August. You will own the engagement end to end: client relationship, solution direction, and delivery, working with a senior AI engineer and the client's R&D, data, and consumer-research stakeholders.

Responsibilities:

• Own the client relationship: run alignment workshops, steer expectations, and translate stakeholder feedback (R&D engineering, consumer research, brand/GM) into scoped backlog items;
• Drive the solution architecture of the 4-agent system (Discovery, Ideation, Validation, Orchestration & Synthesis) - agent design, retrieval strategy, validation gates, human-in-the-loop flows;
• Lead the evaluation program: golden-question benchmark runs, pass/fail calibration with SMEs, blind idea-quality reviews against human baselines;
• Manage delivery against the PoC plan and pilot milestones; prepare and present decision-ready material (architecture overviews, coverage matrices, roadmaps) at executive level;
• Identify and shape follow-on opportunities (Phase 2: conversational layer, scaled evaluation, additional data sources).

Requirements:

• 5+ years in AI/data consulting or applied AI delivery, with proven client-facing lead experience in enterprise settings;
• Hands-on understanding of LLM application architecture: multi-agent systems, RAG (hybrid dense + keyword retrieval, vector stores such as pgvector), prompt design, and LLM evaluation/benchmarking;
• Ability to bridge business and engineering: comfortable challenging both a data scientist's retrieval setup and a brand manager's success criteria;
• Strong workshop facilitation and executive communication skills; able to condense SME interviews and technical detail into clear decision material;
• Fluent English required; German is a strong plus. Background in R&D, innovation management, or consumer goods is a plus;
• You inherit a well-documented, technically de-risked engagement at its most interesting phase - turning a working pipeline into a validated, expert-trusted ideation tool - with a clear path to a larger Phase 2.