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.

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.

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.

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

• Proven experience delivering AI solutions into production, ideally in enterprise or regulated environments.
• Strong software engineering fundamentals (Pythonessential).
• Experience with cloud AI services and modern data platforms (e.g. Azure AI Foundry, Azure ML, Databricks, Amazon SageMaker, Bedrock, etc.).

• 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.

What You'll Gain

• Opportunity to shape and deliver cutting-edge AI solutions across multiple sectors.
• Exposure to Microsoft Azure ecosystem, Databricks, AI Foundry, and the newest agentic/LLM approaches.

• Leadership opportunities within a growing AI practice that values continuous learning, experimentation, and responsible innovation.