• Comprehensive Design Leadership: Lead the design process for information systems, including tool selection, technical visualization, and detailed design documentation, ensuring alignment with customer needs and business objectives. • Incorporate frontend and backend programming technologies, SQL / NoSQL databases, on-premises / cloud infrastructure, intranet/extranet networking technologies, ensuring security and regulatory compliance standards. • Physical Design Translation: Effectively translate logical designs into physical implementations, considering environmental constraints, performance requirements, and existing system integration. • Strategic Leadership: Act as a primary influencer among team members, clients, and suppliers, guiding resource allocation and strategic decision-making to align with broader project and organizational goals. • Proactive Communication: Champion robust collaboration among stakeholders across technological and non-technical domains, facilitating effective communication and alignment on project objectives and methodologies. • Advocacy for Best Practices: Advocate for best practices within software development and architectural design, upholding high standards in client interactions, and ensuring continuous alignment with all parties on design methodologies that meet common objectives and project goals. • Complex Landscape Navigation: Navigate complex social and technical landscapes, making judicious decisions that balance competing interests and priorities.

Role Description The AI/ML Practice Architect is a senior, hands-on technical leader who combines solution architecture and customer consultation with deep applied AI/ML engineering capability. This role accelerates practice growth by shaping repeatable offerings, guiding delivery excellence, and building production-grade AI systems — especially GenAI/LLM, retrieval, evaluation, and agentic workflows — integrated into customer platforms. This role will travel as needed, which includes customer onsite workshops, executive presentations, delivery kickoffs, and internal practice events. Why This Role Exists - Drive measurable customer outcomes by designing and delivering AI/ML and GenAI solutions end-to-end (discovery → build → deploy → operate). - Scale TGS AI capabilities through reusable playbooks, reference architectures, accelerators, and enablement. - Partner with Sales and Delivery to shape, price, and win work; serve as a trusted advisor in pre- and post-sales engagements. Key Outcomes (First 6–12 Months) - Establish (or evolve) the AI/ML Solution Playbook: discovery templates, context/RAG patterns, evaluation rubrics, and governance/guardrails. - Deliver 2–4 production deployments (or major releases) demonstrating reliability, safety, and business value; publish reusable artifacts to the practice repository. - Create a reference architecture for agentic AI/LLM systems (tool use, memory, orchestration, human-in-the-loop controls, observability). - Improve delivery predictability: clear estimation models, quality gates, and SDLC/MLOps/LLMOps standards aligned to DevOps principles. - Support GTM: contribute to proposals, SOWs, pricing, case studies, demos, and executive narratives that help land-and-expand accounts. Core Responsibilities - Practice Architecture & Consulting (Customer Value + Growth): - Lead customer discovery and value definition: map current/future-state workflows, define success metrics, and translate business goals into technical requirements. - Design solution architectures and delivery approaches; document assumptions, risks, dependencies, and cost/effort estimates. - Create and maintain practice solution content: reference architectures, accelerators, templates, delivery playbooks, and pricing guidance. - Partner with Sales, Solutioning, Delivery Leadership, and Practice Directors on pre-sales strategy, proposals, and executive communications. - Mentor consultants/engineers: design reviews, technical coaching, and best-practice enablement across engagements. - Continuously optimize delivery processes, promote reuse, and champion innovation rooted in measurable customer impact. - AI/ML Engineering & Delivery (Hands-on Technical Leadership): - Build and ship production AI/ML systems including model integration, data pipelines, services, and user experiences. - Design and implement GenAI/LLM solutions: prompt & context engineering, RAG grounding, embedding/vector store strategies, and latency/quality trade-offs. - Evolve prompted workflows into agentic AI: durable execution, tool use, memory, orchestration (single- and multi-agent), and human-in-the-loop gates. - Establish evaluation and experimentation rigor: offline/online tests, human + AI evaluation rubrics, error taxonomies, and KPI instrumentation. - Implement security, safety, and compliance controls: PII handling, prompt-injection mitigations, model risk management, and red-teaming. - Operationalize MLOps/LLMOps: CI/CD, model/version management, observability, drift/feedback loops, and incident response. - Leadership, Accountability & Cross-Functional Influence: - Drive execution cadence with clear gates, owners, and KPIs from discovery through launch. - Hold self and others accountable to commitments; proactively resolve issues before they impact customers. - Communicate trade-offs, impact, and risk to technical and non-technical stakeholders; produce executive-ready narratives and artifacts. - Support practice hiring/interviewing and capability building as needed; contribute to internal communities of practice. Qualifications - 8 or more years in full stack software engineering, data engineering, ML engineering, or applied AI, including delivery in customer-facing or consulting environments. - 3 or more years building and deploying ML/LLM/GenAI-powered products (e.g., prompt/context engineering, RAG, evaluation, and guardrails). - Strong solution architecture skills: requirements gathering, estimation, system design, and leading technical decisions across teams. - Proficiency in Python and at least one of: TypeScript/JavaScript, Java, Go, or Rust; experience building APIs and services (e.g., FastAPI, Django, Node/Express). - Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker); familiarity with Kubernetes is a plus. - Ability to influence across stakeholders (Sales, Delivery, Engineering, Product, Security/Privacy) and communicate effectively at multiple levels. Preferred Qualifications - Experience deploying or fine-tuning open-source LLMs (e.g., Hugging Face, vLLM, Ollama) and/or using managed services (e.g., Azure OpenAI, Bedrock, Vertex AI). - Hands-on experience with agent frameworks/orchestration (e.g., LangGraph, AutoGen, CrewAI) and tool integration patterns. - Experience with vector databases and semantic search (e.g., Pinecone, Weaviate, Chroma) and advanced RAG/knowledge graph techniques. - Experience leading small teams or technical workstreams while remaining hands-on. - Exposure to regulated environments (e.g., Finance & Healthcare) and formal security/privacy review processes. Success Profile (Competencies & Behaviors) - Manages Complexity: Integrates diverse inputs, clarifies ambiguity, and translates business and technical constraints into actionable architecture and delivery plans. - Customer Focus: Builds trusted relationships, aligns to measurable outcomes, and delivers customer-centric solutions with quantified impact. - Communicates Effectively: Delivers clear multimode communication; explains trade-offs, risks, and “the why” behind decisions to technical and non-technical audiences. - Ensures Accountability: Owns outcomes, meets commitments, escalates early, and drives execution to closure. - Cultivates Innovation: Creates new and better ways for the organization to be successful; promotes reuse and continuous improvement. - Optimizes Work Processes: Designs efficient delivery processes; improves quality through automation, standards, and playbooks. - Nimble Learning / Self-Development: Learns through experimentation, seeks feedback, and stays current with AI/ML and GenAI trends. - Collaborates: Builds partnerships across Sales, Delivery, Engineering, and customer teams to meet shared objectives. - Decision Quality: Makes good and timely decisions using decision criteria, trade-offs, and risk mitigation. - Manages Ambiguity / Situational Adaptability: Operates effectively when the path is unclear; adapts approach to shifting constraints and stakeholder needs. - Drives Results: Consistently delivers results under tough circumstances and focuses on key goals during setbacks. Job Type & Location This is a Permanent position based out of Chicago, IL. Pay and Benefits The pay range for this position is $136,000.00 - $204,000.00/yr. We reserve the right to pay above or below the posted wage based on factors unrelated to sex, race, or any other protected classification. - Medical, Dental, and Vision - Critical Illness, Accident, and Hospital - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available - Life Insurance (Voluntary Life and AD&D for employee and dependents) - Short and Long-Term Disability - Health Spending Account (HSA) - Transportation Benefits - Employee Assistance Program - Time Off/Leave (PTO, Vacation or Sick Leave) Workplace Type This is a fully remote position. Application Deadline This position is anticipated to close on Jun 12, 2026.

Role Description Iron Mountain is seeking a skilled and motivated Lead Enterprise Architect to join our Iron Mountain InSight team. In this role, you will be responsible for the delivery of a robust, Java-based services functionality within the Agile development lifecycle, ensuring the successful build and scaling of enterprise Java Spring Boot applications. The Iron Mountain InSight team is a collaborative, fast-paced group focused on leveraging cutting-edge cloud infrastructure and modern software architectures to build innovative, high-performance products. What You’ll Do - Microservices Development: Design and develop scalable, high-performance back-end microservices using Spring Boot tailored for a cloud-native environment. - Cloud Deployment & Orchestration: Manage the end-to-end deployment pipeline of services onto Google Cloud Platform-managed Kubernetes clusters using Docker and Helm charts. - Data Modeling & Optimization: Architect and optimize PostgreSQL databases to ensure data integrity through Atomicity, Consistency, Isolation, Durability compliance and maintain peak system performance under high load. - Cloud Native Optimization: Utilize Kubernetes features like ConfigMaps, Secrets, and Ingress to build resilient, secure, and self-healing applications. Qualifications - 7+ years of work experience in a technical engineering role with a direct, hands-on software development skill set. - Expert-level proficiency in Java (specifically Java 17 and above), with a deep understanding of object-oriented design, multithreading, and Java Virtual Machine tuning. - Extensive experience with the Spring Framework ecosystem, including Spring Boot for building Representational State Transfer Application Programming Interfaces, Spring Data Java Persistence API for relational database integration, and Spring Security for implementing robust authentication and authorization via Open Authorization 2.0 and OpenID Connect. - Practical experience with Google Cloud Platform services—including Google Compute Engine, Google Cloud Storage, Cloud Structured Query Language, and Identity and Access Management—to deploy and manage scalable applications. - Strong hands-on experience with containerization using Docker and managing Kubernetes pod lifecycles, service discovery, horizontal scaling, and manifests. - Required technical exposure to continuous integration and continuous delivery tools including GitLab, Git, and Jenkins, alongside any Java Integrated Development Environment. - Proven ability to be self-directed, solve complex problems, and communicate effectively with remote team members across various locations within the United States. - Exposure to Elasticsearch or any non-relational database is a distinct advantage. - Bachelor of Science in Computer Engineering, Computer Science, or a related field from an accredited or recognized university. Benefits - Location: Fully remote work. - Day-One Benefits: Enjoy comprehensive health, wellness, and retirement plans with robust benefits starting on your first day of employment. - Empowering Your Balance: Flexible vacation plan and flexible schedules to support your personal and professional well-being. - Continuous Career Development: Elevate your skills through ongoing training, corporate learning resources, and internal advancement opportunities on a global scale. - Compensation & Care: Competitive salary commensurate with your experience, paired with a comprehensive company-wide benefits package.

• Define and maintain the business architecture, capability roadmap, and solution vision for global service scheduling systems, aligned with enterprise and Commercial Operations strategies. • Partner with business process owners, regional service leaders, and cross‑functional stakeholders to design scheduling solutions that enhance both customer experience and operational performance. • Lead the business design and delivery of scheduling system initiatives, including requirements definition, solution design, testing, deployment, and post‑release stabilization. • Drive the transformation from manual and high‑touch scheduling to digital, automated, and self‑service experiences for customers and internal users. • Translate complex business needs into clear, prioritized functional and architectural designs for IT delivery teams. • Collaborate closely with IT teams, system integrators, and software vendors to ensure solutions meet business, architectural, and scalability requirements. • Support prioritization of system enhancements and defect resolution to balance operational stability with strategic capability development. • Coordinate implementation, testing, training, and change management activities to ensure successful adoption across global service organizations. • Partner with analytics and data teams to define reporting and insight requirements that support scheduling optimization and performance management. • Communicate plans, progress, and outcomes effectively to senior stakeholders, including executive‑level audiences.