Architect, Apps & AI

Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Own the Architecture and drive 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. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Ability to step into at‑risk projects, quickly assess issues, and establish a credible path to recovery or exit. Track new technologies to guide strategy. Drive innovation in delivery, assets, and tools for better efficiency. Promote best practices and continuous improvement across teams. Client Engagement & Solutioning Apply design thinking to develop user-centric solutions that also support business objectives, architecture, and project delivery. Collaborate with clients to identify their needs and provide guidance throughout each stage of the project. Participate in pre-sales and solutioning activities by preparing estimates, proofs-of-concept, and technical proposals. Additionally, maintain strong client relationships to ensure satisfaction and ongoing value. 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 modern delivery methodologies (Agile, Scrum, DevOps, etc.). 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. Full Stack Application Engineering * End-to-end design and development of modern web and mobile applications using React, Angular, Next.js, Blazor, or equivalent frameworks Strong backend expertise using .NET / Java / Node.js / Python, with clean architecture, domain-driven design, and API-first principles Experience building microservices and distributed systems using REST, gRPC, event-driven patterns, and asynchronous processing Hands-on expertise with relational and NoSQL databases (Azure SQL, PostgreSQL, Cosmos DB) and performance tuning Strong understanding of state management, scalability, resiliency, and application security Ability to coach and enable teams and customers on effective Copilot usage patterns, prompt strategies, and safe AI‑assisted engineering practices in enterprise environments. Ability to translate business scenarios into production‑grade AI solutions using Azure OpenAI, Azure AI Services, Azure AI Foundry, and custom ML models, with hands‑on delivery of RAG architectures leveraging Azure AI Search, vector databases, enterprise data grounding, and integration patterns. Experience in cost‑aware architecture design, applying cost optimization strategies such as right‑sizing, autoscaling, consumption‑based services, and proactive cost governance. Experience embedding DevSecOps practices into delivery pipelines, including secure coding checks, dependency scanning, secrets management, policy enforcement, and compliance validation. Ability to continuously improve engineering throughput, quality, and system reliability, while maintaining enterprise security and compliance expectations. * 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 * 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 Side‑by‑side coding with customer engineering teams to unblock deployments and accelerate time to value Outcome‑driven engineering focused on business impact, not activity 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, TDD, and observability practices. 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 Apply Responsible AI principles across design and delivery, incorporating security, privacy, governance, and compliance controls into production‑grade engineering workflows. Designs enterprise‑ready AI solutions with built‑in observability and operational excellence, including telemetry, prompt tracing, agent behavior logging, model metrics, experimentation, drift monitoring, and cost/performance optimization, while applying Responsible AI principles across security, privacy, governance, and compliance - balancing speed, quality, and enterprise constraints at scale. Design and implementation of architectures that support high availability, horizontal scalability, disaster recovery, and fault tolerance, including multi‑region deployment patterns and resiliency strategies. Advance modern methodologies like Agile, DevOps, and CI/CD for scalable solutions. Build a team culture of technical rigor, innovation, and accountability.