Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ability to step into at‑risk projects, quickly assess issues, and establish a credible path to recovery or exit. Apply AI-driven design for user-focused solutions that support business, architecture, and delivery goals. Assess modern technologies to guide strategy. Client Engagement & Solutioning Engage with clients to assess their needs and provide guidance throughout projects. …
Responsibilities
Embed AI-first mindset into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Ensure delivery models are optimized for modern AI-native execution, including integration of automation and intelligent processes. Drive innovation in delivery methods and reusable tools to boost efficiency. Promote best practices and continuous improvement across teams.
Required Qualifications
20+ years of experience in software/solution engineering, with at least 10-15 years as Architect and Delivery leadership roles. Proven experience in leading delivery of complex, multi-disciplinary projects. Strong understanding of delivery methodologies (Agile, Scrum, DevOps, etc.) and adopt emerging practices for faster Go To Market (GTM) using Hyper Velocity Engineering Excellent communication, stakeholder management, problem-solving, and team leadership skills. Bachelor's degree in computer science, Engineering, or related field (or equivalent experience). Relevant certifications are a plus. Enterprise Data Architecture & Modern Platforms Lead enterprise data modernization initiatives in close collaboration with Customer, team and Enterprise Architects, spanning assessment, target‑state design, and optimization. Partner with Customer teams, cross functional Architects on workload characterization, environment separation, capacity planning, balancing performance, scalability, resilience, and total cost of ownership. Share accountability with Delivery Managers, Development team for production rollout, owning performance outcomes, operational stability, and long‑term sustainability through continuous optimization and issue resolution. Lead technical solutioning, estimations, and support architecture design during pre-sales and delivery shaping. Translate business outcomes into clear architecture, execution plans, and risk mitigation strategies. Influence technical direction across multiple teams and engagements. Act as a trusted advisor to clients and internal leadership Full Stack Engineering Lead rapid prototyping, pilots, and early-stage deployments for enterprise customers Ability to go from whiteboard to production with minimal friction Strong troubleshooting and production support expertise, including performance, reliability, and security issues Outcome driven engineering focused on business impact, not activity Adopt Hyper Velocity Engineering (HVE) methodology for rapid production deployment of AI Services Building reusable assets, accelerators, and reference implementations Comfortable operating in ambiguous, high-pressure environments with C-Level customer stakeholders Ability to interact confidently with senior leaders and clients. Establish secure coding, test-driven development, observability, and performance standards as defaults. Support ongoing learning and certifications to stay current. Ensure secure, compliant, and reliable solution delivery through secure coding, test driven‑ development, observability, design reviews, and quality gates across all engagements. Other Embody our culture and values Perform query tuning, execution plan analysis, indexing strategy design, wait state analysis (e.g., CXPACKET), and storage/I/O optimization. Design and implement agentic AI workflows that assist in data discovery, preparation, profiling, validation, and performance optimization. Architecture definition to integrate AI and ML workloads into data platforms, including performance tuning and cost optimization. Design, lead to implement, and optimize solutions using AI Agents where viable using Azure Machine Learning, Azure OpenAI, and Azure AI Services, including RAG pipelines and inference workloads. Ensure AI and analytics solutions are grounded help improving trust, explainability, and relevance of AI outputs. Ensure Responsible AI principles are applied in all AI solutions.
Original Posting
This role is sourced from Microsoft. Apply on Microsoft careers page