• The candidate should have existing Software System deployment experience. • Making our systems and solutions hybrid ready is a key component of the practice office. • Collaborate with field teams to deploy software solutions. • Present and train others on technical processes as the position requires. • Work in high-security areas governed by the US Department of Justice "Criminal Justice Information Services (CJIS) Security Policy". • Pass a more stringent fingerprint background check.

• Serve as the primary technical expert between NVIDIA and our ecosystem • Partner externally with developers, researchers, technology specialists, IT professionals and executives to facilitate the integration of NVIDIA technology • Partner internally with engineering, product and research

Role Description As a Solutions Architect, you will design and implement production-grade AI agents and multi-agent systems that use tools, call APIs, reason over enterprise data, and power modern mobile, web, and Power Platform experiences. We will count on you to be a hands-on delivery consultant focused on building AI & Agentic AI applications. Along the way, you will get to: - Design and implement agentic AI systems using Microsoft Foundry (tool/function calling, multi-step and multi-agent workflows). - Build and manage tools and connectors along the agentic chain (MCP-based tools, custom tool APIs, enterprise integrations). - Develop RAG and data-centric AI capabilities using Azure AI/Cognitive Search and other data sources. - Implement prompt strategies, guardrails, and evaluation loops to improve reliability, safety, and quality. Qualifications - 6+ years of professional software development, including 2+ years in a senior/lead role. - Advanced C#/.NET experience building production APIs and services. - Advanced React + TypeScript front-end development experience. - Hands-on experience delivering solutions on Microsoft Azure (App Service/Functions, Storage, Key Vault, monitoring). Benefits - Freedom to work from another location—even an international destination—for up to 30 consecutive calendar days per year. - Core values of Hunger, Heart, and Harmony, guiding relationships with teammates, partners, and clients.

• Participate in and facilitate requirements gathering activities such as discovery sessions, interviews, and workshops. • Document and validate requirements, including problem statements, success measures, constraints, assumptions, and risks. • Architect and design enterprise application solutions. • Assess current systems management practices. • Perform service level agreement negotiation and documentation. • Prepare and deliver client-ready presentations (findings, options, recommendations, prototypes, and progress updates). • Translate business needs into AI use cases, including value hypotheses, feasibility considerations, and ethical/risk considerations. • Support stakeholder alignment by summarizing trade-offs (e.g., accuracy vs. explainability; cost vs. performance; build vs. buy). • Contribute to project artifacts such as meeting notes, decision logs, RAID logs, and statements of work content (as directed). • Assist with solution design activities including: data understanding and readiness assessment (high level), feature / signal brainstorming, evaluation approach definition (metrics, baselines, acceptance criteria), model/service integration considerations (APIs, workflows, monitoring needs). • Support the creation of prototypes / proofs of concept using approved tools and patterns (e.g., prompt prototypes, small ML experiments, retrieval approaches). • Help define and execute experiments: test plans, evaluation datasets (where provided/approved), and results summaries. • Contribute to technical documentation (solution overview, model cards/AI notes, evaluation summaries, runbooks) at an appropriate level for the audience. • Follow organizational standards for security, privacy, and responsible AI practices as defined by project governance. • Research emerging AI capabilities and patterns relevant to client problems (e.g., agentic workflows, RAG approaches, evaluation techniques). • Run structured experiments to compare approaches and document what worked, what didn’t, and why. • Contribute reusable assets such as templates, checklists, demo scripts, prompt libraries, and “lessons learned” write-ups. • Lead a small pod/workstream of AI specialists (e.g., 1–3 people) on well-scoped tasks by: clarifying goals and deliverables, coordinating work and dependencies, facilitating short stand-ups/check-ins, ensuring quality and timely completion. • Collaborate effectively in a matrixed environment with engineers, analysts, product owners, and client stakeholders. • Seek mentorship and provide peer support through knowledge-sharing and constructive feedback. • Support delivery management by maintaining task status, raising risks early, and helping keep work aligned to timelines. • Contribute to estimates for small tasks (effort ranges, assumptions) and track progress against commitments. • Assist with proposal/support materials (e.g., case study summaries, demo packaging) when needed.