Intellias
Senior Director, AI Solutions
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Over 20 years of market experience, Intellias brings together technologists, creators and innovators in Europe, North and Latin America, and the Middle East. Join our international team and take the mission to solve the advanced tech challenges of tomorrow!
We are building a market-leading AI Solutions practice and are looking for a senior leader to anchor it across Europe. This is a hands-on leadership role at the intersection of technical depth, client advisory, and commercial growth. You will work with business segments and co-own AI outcomes end to end — from shaping opportunities and advising client executives, through architecting and delivering production-grade solutions, to building the team and offerings that let us scale.
This is not a pure management role and not a pure architect role. The right person can sit with a client CTO in the morning to frame a transformation roadmap, dive into a model architecture or agent design review in the afternoon, and shape the next quarter's offering and pipeline in between. You will be a founding pillar of how we take AI from pilot to production at enterprise scale.
Responsibilities
Client Advisory & Pre-Sales
- Act as the senior AI advisor and trusted partner to enterprise clients, translating business problems into pragmatic, value-driven AI strategies and roadmaps.
- Lead pre-sales and solutioning: shape opportunities, scope and estimate engagements, run discovery and design workshops, and present to senior and C-level stakeholders.
- Drive proposal and RFP responses, solution narratives, and commercial framing that differentiate us in competitive situations.
- Identify and grow account opportunities, partnering with business development to convert advisory engagements into delivery programs.
Offering & Practice Development
- Define and productize repeatable AI offerings, accelerators, and reusable assets that shorten time-to-value and improve delivery margins.
- Establish reference architectures, delivery playbooks, and engineering standards for ML, GenAI, and agentic solutions.
- Contribute to AI practice strategy and external thought leadership (points of view, frameworks, speaking, content).
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Delivery Leadership
- Support end-to-end delivery of AI programs — from PoC and pilot through to hardened production — ensuring solutions actually ship and operate, not just demonstrate.
- Drive production readiness across the lifecycle: MLOps/LLMOps, evaluation, monitoring, cost management, security, and AI governance.
- Manage program economics, scope, risk, quality, and stakeholder alignment across distributed delivery teams.
Technical Leadership
- Provide hands-on technical direction across machine learning, deep learning, and GenAI/agentic systems, with the credibility to lead architecture and design reviews.
- Make and defend platform and architecture decisions across hyperscaler and data ecosystems (AWS, Azure, GCP, Databricks, Salesforce etc.).
- Set technical standards and uphold engineering quality, mentoring senior technical staff.
Team Building & Leadership
- Recruit, build, and grow a high-performing AI delivery organization in Europe across data science, ML/AI engineering, and solution architecture.
- Manage, coach, and develop senior practitioners; foster a culture of capability growth, certification, and continuous learning.
- Operate effectively within a collaborative leadership model alongside business development and technology peers.
Requirements
- 12+ years in technology, data, or engineering, with strong hands-on background in AI / ML / data science, including genuine hands-on practice (not solely oversight).
- Demonstrable hands-on expertise in machine learning and deep learning— model development and experimentation with frameworks such as PyTorch or TensorFlow, and a working command of modern ML/DL techniques.
- Proven track record delivering AI/ML solutions into production at enterprise scale — you have shipped systems that operate reliably in the real world.
- Production experience on at least one major hyperscaler or data platform(AWS, Azure, GCP, or Databricks); multi-platform fluency is a strong advantage.
- Hands-on production experience with GenAI and agentic systems — LLMs, RAG, orchestration and agent frameworks, tool/function calling, and evaluation of non-deterministic systems.
- Experience leading both internally and externally — line-managing internal teams and owning external client programs as a delivery lead, engagement lead, or equivalent accountable role.
- Executive-grade client presence — able to advise, influence, and build credibility with senior business and technology stakeholders.
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Nice to Have
- Prior consulting or IT/professional-services experience — pre-sales, offering development, and accountability for running AI projects and programs (including revenue or margin contribution).
- Experience building or scaling an AI / data practice or capability from an early stage.
- Deep domain expertise in one or more priority verticals — e.g., retail, automotive & mobility, financial services, healthcare / medtech & life sciences, or telecom — sufficient to speak the client's language and frame value, not just technology.
- Familiarity with EU AI Act, GDPR, and responsible-AI / governance frameworks as applied to enterprise deployments.
- Relevant certifications (AWS / Azure / GCP ML or AI, Databricks).
- Advanced degree (MSc or PhD) in Computer Science, Data Science, Machine Learning, Engineering, or a related field.
- Experience operating within nearshore / distributed delivery models.
- Additional European languages.
What Success Looks Like (First 6–12 Months)
- Established credibility with key clients and internal stakeholders as the go-to senior AI leader for one or more business segments.
- Shaped and helped win AI engagements, with a measurable contribution to pipeline and bookings.
- Stood up or sharpened a set of productized AI offerings and accelerators that the team can sell and deliver repeatably.
- Promoted delivery and engineering standards and begun building a growing, high-quality AI team with measurable impact
- Delivered (or put firmly on track) at least one flagship AI program running in client production.
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