AI Coach – Agentic AI & Enterprise Adoption

About the role

Help enterprise teams adopt agentic AI safely, effectively, and at scale by combining technical expertise with coaching, facilitation, and advisory skills to turn AI opportunities into business outcomes.

Key responsibilities

• Coach teams and leaders on adopting AI agents and agentic workflows.
• Establish AI governance, guardrails, and responsible AI practices.
• Support design of AI solutions with tracing, evaluations, observability, and quality controls.
• Facilitate architecture discussions, workshops, and AI strategy sessions.
• Enable software and platform teams to implement AI capabilities using modern cloud‑native practices.
• Capture architectural decisions, patterns, and best practices through ADRs and reference architectures.
• Drive AI literacy and change management across technical and business stakeholders.

Required profile

• Strong facilitation and coaching skills, comfortable mentoring developers, architects, product owners, and leadership.
• Ability to translate AI concepts into actionable guidance for engineering and business stakeholders.
• Excellent communication and presentation skills in English and Finnish.

Required skills

• Experience with agent frameworks such as Microsoft Agent Framework, OpenAI Agents SDK, LangGraph.
• Knowledge of Retrieval‑Augmented Generation (RAG), AI evaluations, observability, tracing, and quality assurance.
• Deep Azure background (AI Foundry, Container Apps, API Management, Key Vault, identity, networking).
• Infrastructure‑as‑code using Bicep or Terraform.
• Familiarity with GitHub, CI/CD pipelines, and modern software engineering practices.
• Understanding of AI governance, policy enforcement, security controls, compliance, and zero‑trust principles.

What we offer

• Professional growth, meaningful work, open culture and strong work‑life balance.
• Opportunity to shape the future of a fast‑developing AI sector.
• Flexible hybrid work model.
• Culture that encourages curiosity, continuous learning and unlearning.