Practice Director, Data & AI - Remote US Only

Blue Mantis•,

8d•$200,000 - $230,000•Remote

About The Position

The Practice Director, Data & AI leads the Data & AI practice within the Presales & Solution Architecture function and reports to the Chief Technology Officer, SVP. The role owns the practice’s strategy, commercial and operational performance, and talent agenda across Data Modernization & Governance, AI Transformation & Solutions, and Data Infrastructure & Operations. It combines technical leadership with business acumen to grow pipeline, deliver customer outcomes, and build delivery readiness for mid-market clients, using a partner-led approach anchored by Microsoft and complemented by other data, AI, and infrastructure platforms. The Director develops standardized offerings, solution assets, sales plays, reference architectures, governance models, delivery standards, and partner relationships. The practice is positioned around an integrated customer story: modernize the data estate, put AI to work, and run AI securely and economically. The role translates customer needs, partner capabilities, AI adoption trends, security and governance requirements, and delivery capabilities into repeatable solutions and measurable outcomes. It collaborates closely with sales, delivery, operations, and adjacent practices to achieve deal success and long-term practice maturity.

Requirements

10+ years of experience in IT architecture, presales, or consulting.
3+ years leading a practice, presales team, or advisory function in data, analytics, or AI.
Demonstrated success building and managing practices or technical teams.
Direct experience leading professional services, presales, delivery, or advisory functions in data, analytics, or AI practice areas.
Experience with leading OEMs, ISVs, and the professional services industry.
Demonstrated success delivering complex customer programs, solution implementations, or transformation initiatives relevant to data modernization or applied AI.
Experience helping mid-market customers modernize data estates, apply AI to business outcomes, and operate AI securely and economically using Microsoft and other leading platforms.
Demonstrated success embedding repeatable methods, automation, governance, enablement, or operational discipline into customer programs and internal practice execution.
Deep expertise in data and AI solution architectures, with broad knowledge of adjacent cloud, infrastructure, and security domains.
Experience developing go-to-market strategies, standardized offerings, and delivery frameworks for data modernization, analytics, and AI solutions.
Ability to manage financial and operational performance metrics.
Strong understanding of data architecture, integration, governance, and quality patterns, and AI solution design including RAG, agentic workflows, and generative AI applications.
Working knowledge of AI infrastructure, security, and operations topics—including GPU and accelerated compute, AI-ready virtualization, AI security, responsible AI, AI FinOps, and AI observability—sufficient to shape offerings and pursuits delivered with adjacent practices.
Strong understanding of mid-market customer environments, common challenges, adjacent technology domains, and relevant operating considerations.
Hands-on experience with methods, tools, frameworks, and operational practices commonly used to deliver data and AI solutions.
Strong leadership and interpersonal skills, with the ability to influence executives and cross-functional stakeholders across sales, delivery, and adjacent practices.
Demonstrated ability to build and scale technical teams in presales or practice management functions.
Strong communication and presentation skills for explaining complex data and AI concepts to technical and business audiences.
Bachelor’s degree in Computer Science, Business, or a related field, or equivalent experience.

Nice To Haves

Architectural experience with Microsoft Fabric, Azure data services, Power BI, and Azure AI Foundry, as well as other leading cloud data and AI platforms.
Industry-recognized data and AI certifications, such as Microsoft DP-600, DP-700, or AI-102, or equivalent credentials from other leading cloud and data platform vendors.

Responsibilities

Define and execute the Data & AI practice strategy in alignment with company objectives, mid-market customer needs, partner and technology roadmaps, and market demand.
Develop and maintain standardized offerings, reusable assets, solution blueprints, productized pitch materials, labor models, qualification patterns, and scalable partner-aligned sales motions.
Own the offer and pursuit narrative for Data Modernization & Governance, including data strategy and maturity assessments, architecture and modernization, integration and engineering, governance, quality, literacy, lineage, cloud data platforms, analytics, business intelligence, and data estate discovery and rationalization.
Own the offer and pursuit narrative for AI Transformation & Solutions, including readiness assessments, strategy and roadmaps, use-case identification, Copilot readiness and adoption, AI agents and agentic workflows, RAG and enterprise knowledge solutions, intelligent automation, custom generative AI applications, and adoption and change enablement.
Own the offer and pursuit narrative for Data Infrastructure & Operations, including AI infrastructure, GPU and accelerated compute, AI-ready virtualization, hybrid and private AI environments, AI security and red teaming, responsible AI and governance, data protection, AI FinOps, observability, model and agent lifecycle management, and managed AI environments.
Align offerings with existing Blue Mantis capabilities and define working boundaries with Microsoft & Modern Workspace, Cybersecurity, Datacenter Modernization, and Strategic Advisory Services.
Establish reusable reference architectures, solution patterns, governance models, delivery standards, practice accelerators, and enablement assets for data platforms, RAG, agentic workflows, and AI operations.
Drive go-to-market strategy and cross-functional collaboration to accelerate growth and attach Data & AI offerings to broader cloud, security, and managed services engagements.
Collaborate with delivery leadership to refine methodologies, standards, governance models, and automation-first practices that improve delivery quality, speed, consistency, and operational outcomes.
Provide deal leadership and escalation support for complex or high-value Data & AI opportunities.
Lead customer-facing architecture, discovery, proposal strategy, executive pursuit support, solution narrative development, seller enablement, qualification guidance, objection handling, and field activation for strategic opportunities.
Shape opportunities that expand practice revenue, increase managed or recurring service adoption, and strengthen customer relationships.
Collaborate with sales teams to review solution architectures, validate alignment, and close strategic pursuits.
Advise customers on data and AI strategy, readiness, governance, AI use-case prioritization, Copilot and agent adoption, and secure, cost-controlled AI operations using phased roadmaps.
Support multi-year transformation programs, including business cases, value modeling, investment roadmaps, and phased execution plans.
Guide executive stakeholders on business impacts, data ownership, governance, operating model changes, responsible AI, risk reduction, and cost control.
Position data readiness, governance, and measurable business outcomes as value drivers in customer business cases and sales pursuits.
Represent and promote the practice internally, with clients, and at industry events; support automation of presales processes.
Build, lead, and develop the Data & AI solution architect team, defining role expectations, team structure, and hiring plans.
Manage practice capacity, workload, resourcing, presales coverage, skills, and utilization in line with growth goals and demand.
Recruit, mentor, and develop team members through career paths, training, and certification roadmaps; build a collaborative, high-performing culture.
Partner with delivery leadership to forecast demand and plan internal staffing, skills-gap remediation, subcontractor capacity, and partner capacity to support quality and margin.
Ensure presales talent can explain technical and business impacts, customer outcomes, operational considerations, and adoption requirements.
Lead strategic partner alignment, including joint account planning, co-selling, funding alignment, solution plays, and partner business reviews across Microsoft and other data, AI, and infrastructure vendors.
Guide partner specializations, designations, delivery and tooling partnerships, and ecosystem capabilities to support market demand, funding, delivery scalability, and margin.
Maximize vendor, alliance, and distributor programs, incentives, funding, and customer adoption opportunities.
Coordinate partner investments and field motions with sales, delivery, PMO, Partner Alliances, CSP, Managed Services, Security, Marketing, and Finance.
Incorporate partner platforms, tools, and enablement into joint go-to-market strategies, offerings, accelerators, campaigns, and solution plays.
Track and report financial and operational KPIs, including pipeline health, win rates, utilization, revenue, margin, managed-service attachment, and customer adoption.
Use reporting and feedback to refine practice strategy and advise leadership through business reviews, strategic account reviews, and operating cadences.
Maintain pipeline hygiene, forecast quality, CRM discipline, opportunity data integrity, and operational reporting.
Adhere to bi-weekly, monthly, and quarterly governance cadences and accountability processes.