Director- Applied AI & Machine Learning (SME)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director- Applied AI & Machine Learning (SME) based in United States.

This is a senior, client-facing leadership role focused on shaping and delivering high-impact AI and machine learning solutions on the Microsoft <platform.You> will act as a trusted technical advisor, translating complex business challenges into compelling Data & AI architectures and measurable outcomes.The role combines strategic consulting, solution architecture, pre-sales leadership, and hands-on technical expertise across Azure AI and data <technologies.You> will partner closely with sales and account teams to qualify opportunities, influence major deals, and guide engagements from discovery through <close.You> will engage directly with technical practitioners and C-suite stakeholders, bringing strong executive presence and architectural depth to critical <conversations.You> will also mentor architects and data scientists while helping establish reusable accelerators, reference architectures, and delivery playbooks.This is an opportunity to influence enterprise AI strategy while working in a collaborative, fast-moving environment centered on innovation and client impact.

Accountabilities

Lead AI & ML strategy: Act as a technical evangelist and trusted advisor, shaping early-stage client conversations into compelling AI and machine learning solution visions built on Microsoft technologies.

Drive pre-sales engagements: Partner with sales and account teams on opportunity qualification, solution strategy, pipeline development, proposals, and deal closure, including engagements involving $1M+ opportunities.

Lead technical discovery: Conduct client discovery sessions to understand business priorities, decision criteria, value drivers, and technical requirements, translating findings into end-to-end Data & AI architectures.

Design and present solutions: Own the technical design of AI and ML solutions and communicate their business value, technical feasibility, ROI, security, governance, and scalability through whiteboarding, architecture reviews, and executive presentations.

Provide executive-level advisory: Engage confidently with technical teams and C-suite stakeholders, establishing credibility and serving as a strategic technical partner throughout the sales cycle.

Guide technical teams: Mentor architects and data scientists, promote technical excellence, ensure architectural consistency, and support team members in independently leading pre-sales and delivery advisory engagements.

Develop growth opportunities: Identify opportunities for innovation workshops, proofs of value, targeted thought leadership, and other initiatives that expand the AI and Data pipeline.

Strengthen AI capabilities: Lead the development and adoption of platform accelerators, reference architectures, and delivery playbooks aligned with Microsoft Data & AI offerings.

Maintain technical leadership: Stay current with Microsoft Data & AI roadmaps, emerging AI/ML trends, competitive developments, security standards, and regulatory requirements to continuously improve client solutions and positioning.

Requirements

Senior industry experience: 10+ years of experience across Data Science, AI, Data, or Analytics, with substantial experience working in enterprise client environments.

Pre-sales and consulting expertise: Proven success leading client-facing technical engagements involving discovery, solution design, architecture, executive presentations, and commercial progression.

Microsoft Data & AI expertise: Deep hands-on experience with Microsoft technologies, with strong expertise in at least one of Azure Data Services, Azure AI, Synapse/Fabric, or Databricks on Azure.

AI and architecture skills: Strong architectural mindset and ability to design secure, governed, scalable, end-to-end Data & AI solutions aligned with client objectives.

Commercial impact: Demonstrated success partnering with sales and account teams to influence pipeline progression and close $1M+ deals.

Executive presence: Comfortable engaging C-suite and senior business leaders as a trusted technical advisor and leading high-level technical and strategic discussions.

Business communication: Exceptional ability to translate sophisticated technical concepts into clear business value narratives for both technical and non-technical audiences.

Presentation and storytelling: Strong whiteboarding, storytelling, facilitation, and formal presentation skills.

Leadership and mentoring: Ability to guide, develop, and motivate architects and data scientists while raising the technical standard across teams.

Adaptability: Comfortable operating in a fast-paced environment, managing ambiguity, and balancing strategic priorities with execution.

Work authorization: Must be legally authorized to work in the United States; visa sponsorship is not available for this position.

Benefits

• Base salary: $168,400–$252,600 USD, with final compensation determined by skills, education, experience, and geographic location.
• Additional compensation: Eligibility for an annual discretionary and/or utilization-based bonus, depending on the role.
• Flexible work: Virtual-first approach with flexible work location.
• Retirement: 401(k) plan with a company match of up to 50% of the first 6% of eligible contributions.
• Paid time off: Minimum of 15 days of PTO, plus 9 paid company holidays and 2 floating personal days.
• Healthcare: Choice of two medical plan options, plus optional dental and vision coverage.
• Insurance: 100% employer-paid life and disability insurance.
• Family support: Paid leave for both birth and non-birth parents.
• Flexible spending: Healthcare FSA, HSA, and Dependent Care FSA options.
• Remote-work support: $67 monthly technology and home-office allowance.
• Employee support: Employee Assistance Program for everyday personal and professional challenges.
• Growth and impact: Opportunities to work on complex enterprise AI initiatives, develop reusable technology capabilities, and influence client strategy.
• Inclusive culture: A collaborative environment that values diverse perspectives, experimentation, candid feedback, professional growth, and shared accountability.