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Dufrain is a pure-play data consultancy specialising in helping businesses unlock the true value of their data by providing market-leading data solutions and services which includes developing strategies for AI readiness, improving data literacy and culture, enhancing real-time reporting, and managing data from mergers and acquisitions.
We are seeking an AI Engineering Lead who combines strong consulting, communication, and stakeholder engagement skills with deep technical expertise. You will translate complex AI concepts into clear, actionable direction for senior business and technical audiences, shaping client thinking and ensuring solutions deliver real business value.
In this role, you will lead and grow a high‑performing AI engineering team, setting engineering standards, guiding delivery quality, and providing hands‑on technical leadership across multiple projects. You will ensure solutions are robust, scalable, responsibly designed, and aligned to client needs, acting as a trusted advisor to help clients understand AI opportunities and make confident delivery decisions.
This is a client‑facing, engineering‑led position suited to someone with strong curiosity, a passion for emerging technologies, and a proven track record of taking AI solutions into production.
Consulting & Communication Skills
- Proven ability to engage, influence, and build trust with senior stakeholders, both technical and nontechnical.
- Exceptional communication skills, able to simplify complex concepts and guide discussions with clarity, empathy, and authority.
- Experience leading workshops, shaping solution options, and supportingdecision-makingin ambiguous orhigh stakesenvironments.
- Strong consulting mindset: structuredproblem-solving, ability to frame challenges, articulatetrade-offs, and align teams around a shared approach.
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Leadership & Delivery
- Experience overseeing the technical delivery of projects, guiding engineers, and holding delivery teams to high-quality engineering standards.
- A proactive, accountable mindset with the ability to structure work, identify risks early, and drive solutions.
Technical Expertise
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Proven experience delivering AI solutions into production, ideally in enterprise or regulated environments.
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Strong software engineering fundamentals (Pythonessential).
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Experience with cloud AI services and modern data platforms (e.g. Azure AI Foundry, Azure ML, Databricks, Amazon SageMaker, Bedrock, etc.).
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Practical understanding of MLOps practices, including CI/CD, IaC, model monitoring, and operational observability.
Personal Attributes
- Strong consulting presence with the ability to command a room, communicate with clarity, and guide client decision-making with confidence and empathy.
- Passion for learning, particularly emerging AI technologies.
- Collaborative team player who enjoys mentoring others.
Practice & Leadership
- Define and uphold engineering standards across the AI capability.
- Coach and mentor AI engineers, shaping a high-performing and collaborative team.
- Contribute to capability strategy and the development of reusable patterns and accelerators.
Client & Consulting Responsibilities
- Act as a trusted advisor to clients, translating complex AI and technical concepts into clear, business relevant language that supports confident decision-making.
- Lead client conversations, workshops, and architecture/design sessions, ensuring objectives are clarified, expectations aligned, and stakeholders guided through trade offs.
- Shape solution options and delivery approaches with a consulting mindset, ensuring recommendations are grounded in value, risk awareness, and responsible AI principles.
- Support AI roadmap development and contribute to pre‑sales and account growth.
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Technical Delivery & Engineering
- Architect, build, and deploy AI/ML and agentic solutions into production environments.
- Provide hands‑on technical leadership across delivery teams, ensuring engineering quality, security, scalability, and maintainability.
- Implement production-grade patterns: CI/CD, testing frameworks, model registries, observability, and responsible AI guardrails.
- Design and implement robust model evaluation and monitoring processes, covering performance, drift detection, data quality, safety, and operational reliability.
- Introduce and operate human-in-the-loop (HITL) mechanisms for higher risk workflows, ensuring appropriate oversight and continuous improvement.
- Integrate solutions with cloud and data platforms and enterprise systems.
Innovation & Continuous Learning
- Rapidly onboard new AI technologies, frameworks, and techniques and share knowledge across the team.
- Evaluate new tools (e.g. agent frameworks, prompt engineering patterns, vector databases, orchestration tools) and drive adoption.
What You'll Gain
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Opportunity to shape and deliver cutting-edge AI solutions across multiple sectors.
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Exposure to Microsoft Azure ecosystem, Databricks, AI Foundry, and the newest agentic/LLM approaches.
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Leadership opportunities within a growing AI practice that values continuous learning, experimentation, and responsible innovation.
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