Architect, Delivery Operations & AI Systems

Responsibilities

• Architect enterprise delivery solutions for complex business and scientific workflows, including software platforms, automation pipelines, integrations, and AI-enabled operational capabilities.
• Define end-to-end architecture patterns for agentic and traditional systems, including orchestration, tool integration, event-driven services, APIs, cloud-native components, and enterprise data connectivity.
• Lead design of LLM- and agent-based capabilities, including prompting/orchestration strategies, memory and context handling, retrieval-augmented generation (RAG), understanding of Model Context Protocol (MCP) structures and human-in-the-loop decision pathways.
• Establish architecture guardrails for safety, security, compliance, observability, reliability, and cost management across AI and application delivery platforms.
• Provide senior technical consultation to Delivery Operations leadership, product teams, software engineers, and business stakeholders on architecture decisions, technology selection, and implementation tradeoffs.
• Design for operational resilience, including monitoring, telemetry, fallback mechanisms, access control, prompt injection protection, and service recovery patterns.
• Drive cloud, DevOps, and MLOps architecture standards, including CI/CD pipelines, containerization, serverless workloads, message-based processing, and scalable runtime environments.
• Evaluate emerging technologies and translate them into pragmatic, business-relevant architecture recommendations that improve productivity, delivery speed, quality, and risk management.
• Lead cross-functional architecture alignment across product management, software engineering, data science, platform teams, and support organizations to ensure cohesive technical direction.
• Mentor engineers and technical leads by promoting architecture best practices, reviewing designs, and helping teams solve highly complex implementation and operational challenges.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Biomedical Engineering, or related field plus 7 years' experience; OR Master’s degree plus 6 years' experience; OR PhD with 2 years’ experience
• Respective years of experience in software engineering, enterprise architecture, solution architecture, or application/platform delivery roles.
• Experience with AI/LLM-enabled systems, agent orchestration patterns, RAG frameworks, or secure enterprise AI architecture.
• Demonstrated experience designing and implementing large-scale enterprise application architectures.
• Strong experience with cloud-native architecture, APIs, distributed systems, event-driven design, and modern software delivery practices.
• Strong understanding of software development lifecycle (traditional and Agile methods), operational support models, and platform reliability principles.
• Experience working in regulated environments and applying security, compliance, and data governance requirements in architecture decisions.
• Proven ability to evaluate emerging technologies and turn them into practical, scalable business solutions.
• Excellent written, verbal, and stakeholder communication skills.