AI Engineer

About

We're looking for a hands‑on AI Engineer who can design, build, and operationalize production‑grade AI systems-while also acting as a trusted technical advisor to clients and a partner to our CTO. This is a role with real impact. You will influence how we architect, standardize, and deliver GenAI solutions across engagements: from discovery and solution design, through implementation, to production hardening and continuous improvement. You'll combine strong engineering fundamentals with consulting skills: framing problems, assessing feasibility, leading technical discussions, and making architectural trade‑offs that stand up to enterprise scrutiny.

Responsibilities

Build & Ship

• Develop and deploy enterprise‑grade GenAI applications: conversational search, RAG systems, multimodal agents, and domain‑specific classification services.
• Build robust data and language‑processing pipelines using Python, LangChain, and cloud‑native components.
• Implement retrieval architectures using Vertex AI Search, Vector Search, or other vector database solutions.
• Optimize GenAI solutions for quality, reliability, latency, and cost-including RAG tuning and targeted fine‑tuning where justified by business value.

Production Readiness

• Define and implement evaluation frameworks: automated tests, regression checks, hallucination/faithfulness indicators.
• Set up monitoring for model performance, app reliability, and business‑aligned KPIs.
• Establish best practices around deployment, versioning, observability, incident reviews, and repeatable delivery patterns.

Advisory & Client‑Facing Work

• Translate business goals into viable, scalable GenAI architectures on Google Cloud - with clear assumptions, risks, and acceptance criteria.
• Lead or co‑lead discovery and feasibility workshops, focusing on use case framing and data readiness within the GCP ecosystem.
• Support presales: providing solution options, delivery approaches, and realistic implementation plans.

What we are looking for

• 2‑5+ years of hands‑on AI/ML development experience, including LLMs and NLP.
• Strong Python engineering skills; practical experience with LangChain, Streamlit, and ML frameworks.
• Solid understanding of RAG architectures and LLM fine‑tuning.
• Familiarity with the end‑to‑end AI/ML lifecycle, evaluation methods, efficiency metrics, and deployment patterns.
• Ability to communicate clearly with both technical and non‑technical stakeholders.
• Proficiency in English.

Nice to have

• Experience delivering AI solutions in consulting environments.
• Awareness of GenAI‑related security considerations: PII, access control, prompt injection, data residency.
• Cloud‑native deployment experience (containers, CI/CD, infra patterns) within GCP.

What we offer

We work with global enterprise clients on high‑impact data & AI initiatives - which means real architectural challenges, technical ownership, and room to grow.

• Remote-first, flexible working model
• Projects involving building modern data & AI platforms from scratch
• Full working equipment
• Regular knowledge‑sharing sessions and mentoring
• Collaboration with international clients (Switzerland, France, UK, US, UAE, and more)
• A real team culture built on trust, autonomy, and high standards
• Team integrations, without the awkward corporate vibe