Tech Stack

Description

You will lead multiple delivery teams and managers, ensuring they are healthy, high-performing, and aligned to service line priorities. You will also lead architecture for large Azure programs spanning applications, platforms, and data, connecting business goals to cloud modernization roadmaps and guiding multi-team execution.

Requirements

• 12+ years of experience delivering solutions in a primary domain such as application development, cloud platform engineering, DevOps, or data and analytics, including significant work at enterprise scale.
• 7+ years of experience in solution architecture and leading development or engineering teams, including multi-team or multi-workstream efforts at program scale.
• Significant experience in data science, machine learning, and Azure data platforms, including 3–5 years in practice or portfolio leadership roles.
• Deep expertise across most of the following domains: Machine Learning MLOps, Data Engineering Integration, Statistical Predictive Modeling, Generative Agentic AI, Data Architecture Governance, Analytics Visualization.
• Proficiency with modern development and collaboration tools (GitHub, Copilot, CI/CD pipelines).
• Established relationships or influence within the Azure and data science ecosystem.
• Relevant Azure or Databricks certifications in Data, AI, or Architecture.
• Proven experience leading architecture and delivery for Azure-based modernization, transformation, AI, or platform programs at enterprise scale.
• Experience defining solution and platform architectures that connect business strategy with scalable technical design, strong delivery practices, and measurable outcomes.
• Experience leading hybrid and remote teams and working with multiple stakeholders across time zones.
• Deep understanding of core concepts, languages, frameworks, and design patterns in a primary domain.
• Experience designing and integrating quality, automation, and observability practices at scale.
• Experience using AI-augmented development and integrating AI and machine learning capabilities into solutions.
• Significant experience working in Agile or Scrum environments at scale.
• Proven success in consulting or professional services, including client-facing leadership and executive engagement.
• Familiarity with key Azure services used in modern solutions.
• Strong analytical and problem-solving skills, with strong presentation, written, and verbal communication skills.
• Commitment to continuous learning in cloud, data, and AI.
• Ability to foster culture, inclusion, and community participation.
• Relevant cloud architecture certifications strongly preferred.

Responsibilities

• Maintain a clear view of each team member's delivery commitments, growth plans, and internal contributions.
• Develop and grow team members through regular coaching, clear expectations, and constructive feedback.
• Build a culture of trust, inclusion, and collaboration.
• Monitor team health, morale, and workload balance.
• Maintain regular one-to-one connections with each team member, provide clear feedback, and help them remove blockers.
• Oversee staffing and resource alignment across teams.
• Communicate practice priorities and organizational objectives clearly.
• Define interview standards and mentorship strategies.
• Create and maintain development plans for team members.
• Lead or support performance reviews, promotion recommendations, and compensation input.
• Represent your teams in leadership forums.
• Lead architecture and technical strategy for large Azure programs and portfolios.
• Define modernization blueprints and reference architectures across applications, platforms, and data.
• Translate business and product strategy into cloud architecture roadmaps and execution plans.
• Guide major architecture decisions across programs.
• Work across teams to connect solutions into cohesive end-to-end architectures.
• Provide architectural oversight during delivery through design reviews, forums, and governance.
• Promote modular design, clear boundaries, testability, CI/CD, and observability.
• Use AI tools to accelerate discovery, design, code, tests, documentation, and analysis.
• Lead or co-lead executive and senior stakeholder conversations on cloud modernization, platform strategy, AI adoption, and program roadmaps.
• Use structured problem solving to clarify scope, dependencies, risks, and trade-offs.
• Set discovery strategy so program objectives flow into a clear, traceable backlog.
• Explain complex architecture and modernization strategies in clear language.
• Build trusted relationships with technology and business leaders.
• Define architecture, discovery, and delivery frameworks and working agreements.
• Align teams on shared outcomes, APIs, integration contracts, and operating models.
• Support effective use of Agile methods at program scale.
• Track risks, technical debt, quality trends, and architectural drift across teams.
• Support cross-practice opportunity qualification and estimating.
• Mentor Senior Architects, Delivery Architects, and senior engineers.
• Provide architectural oversight across programs, modeling pragmatic decision-making.
• Help shape career paths and development plans for architects.
• Create and maintain high-leverage learning assets.
• Support hiring, calibration, and talent development.
• Set a high bar for executive-ready communication and storytelling.
• Help build a culture of psychological safety, inclusion, constructive feedback, and continuous improvement.
• Grow the company by identifying opportunities within your accounts across all our capabilities.
• Intentionally build executive relationships within accounts.
• Drive sales opportunities by participating in pursuit teams.
• Partner with sales, account, and practice leaders to shape technical strategy.
• Lead the creation of solution options, program-level architectures, and estimates.
• Operate as a senior technical advisor.
• Identify follow-on and adjacent opportunities.
• Define and evolve reusable assets.
• Champion adoption of modern frameworks, cloud platform capabilities, automation practices, and AI assisted tools.
• Contribute to internal cross-practice initiatives.
• Shape enablement programs that grow capabilities and reusable assets across accounts.