Who We Are
Umain, part of the Nordic consulting house Eidra, specializes in accelerating top-line growth through digital strategy and innovation. We’re a fast-growing consultancy already partnering with industry leaders—from cutting-edge automotive brands to forward-looking tech companies. Together with Eidra’s 1200+ strategists, creatives, and engineers spread across Stockholm, New York, and beyond, our vision is to drive the integration of AI, ML, and Data Science in businesses. Now, we’re building a dedicated team to define that future—and we want you to help lead the way.
Job Summary:
We are looking for a visionary Tech Director in AI Engineering with a proven track record of leading impactful solutions to head Umain’s AI stream, guiding clients through AI adoption complexities while leveraging your skills to secure deal closures, enhance project delivery, and build a top-tier team that positions Umain as an AI Engineering leader.
What We Offer:
-
A leadership role in defining and executing AI strategy for client projects, whilst exploring and pushing the boundaries of applied AI
- A dynamic and collaborative work environment where you will significantly influence Umain’s AI direction and build an industry-leading team
- The chance to lead multidisciplinary teams in an ambitious setting as you help translate cutting-edge AI concepts into real-world value
- Opportunities for professional and personal growth, supported by unique challenges, fantastic colleagues, and a dedicated personal coach
As a Tech Director, AI Engineering at Umain, your role will involve…
-
Commercial impact
- We expect that you will play a key role in securing major contracts and driving successful deal closures, while also ensuring the team remains at the forefront of the latest AI advancements. That means that you will scale your expertise to:
- Influence clients by establishing trust as a recognized AI authority, seamlessly onboarding them to our methodology, while addressing risks and outlining effective mitigation strategies.
- Shape and scope proposal: what are deliverables, what is in/out scope, how to phase and price this.
Technical Leadership:
-
Lead Umain’s strategy in AI/ML
- Be the client-facing expert
- Represent Umain AI within Eidra
AI Solution Architecture:
-
Architect appropriate AI solutions for clients, ability to understand and communicate trade-offs
- Help teams choose the right tech
- Understand compliance issues for different markets, have your finger on the pulse legal framework development within AI
Client Engagement & Strategy:
-
Be a primary advisor for clients
- Create actionable AI strategies to solve complex business problems/challenges
- Good ability to communicate potential, limitation, suitability and risk around AI frameworks/solutions
Overall accountable for QA and improve deliveries:
-
Drive project success by strategically shaping its scope: breaking down complex challenges into manageable parts, prioritizing the key deliverables, and ensuring high-quality outcomes
- Direct and oversee the journey to production by guiding the team to focus on critical priorities, clarifying roles and responsibilities, identifying and resolving bottlenecks, addressing overlooked details, maintaining clear client communication, and proactively anticipating potential challenges to enhance delivery quality.
- Over time, you’ll establish scalable QA procedures that cater to evolving project demands to ensure consistent excellence and continuous improvement across deliverables
Who You Are:
-
You possess a strong intuition for AI, and understand how to balance trade-offs between its transformative potential and its practical limitations
- You have a proven ability to architect and oversee the delivery of complex, scalable AI solutions that meet concrete business needs
- You thrive in dynamic consultancy environments, enjoy engaging with clients to translate their business needs and contexts into effective AI strategies
- You believe in the power of collaboration and diversity, recognizing the impact you can make by leading and working closely with multi-disciplinary teams
- Familiarity with the modern AI stack (e.g., common frameworks like PyTorch/Tensorflow, concepts like transfer learning, PEFT, multi-modal models, MLOps principles) is essential for guiding architectural decisions
