• Design, implement, and evaluate scalable modular model architectures that allow specialization and efficient use of computation • Develop and test methods that learn richer contextual and temporal representations by predicting or aligning different views, frames, or modalities • Improve representation-learning pipelines by experimenting with data preparation strategies, augmentation approaches, training schedules, and hyperparameter settings to increase robustness across modalities • Build reproducible training and evaluation workflows and run experiments at scale; maintain clear experiment logs and analyses • Measure model effectiveness on clinically relevant downstream tasks (e.g., classification, detection, segmentation, retrieval, temporal reasoning) and produce comparison reports and ablation studies • Collaborate with data engineers, clinicians, and researchers to curate and prepare datasets while following privacy and governance requirements • Produce well-documented code, experiment artifacts, internal reports, and, where appropriate, contribute to technical write-ups or presentations

• Partner with senior and C‑Suite stakeholders to identify “agent‑first” opportunities across business units and define multi‑phase AI Workforce roadmaps tied to clear business outcomes. • Lead the design of complex, production‑grade agentic systems using Snowflake Intelligence (no‑code/low‑code) and Cortex Search/Analyst, emphasizing configuration and semantic modeling over custom code. • Design multi‑step “Reasoning & Acting” (ReAct) flows using Snowflake’s UI, semantic layers, and native apps to orchestrate tools, policies, and data workflows. • Architect high‑accuracy retrieval‑augmented generation (RAG) and knowledge solutions using Cortex Search, with patterns for content onboarding, relevance tuning, evaluation, and continuous improvement. • Advise on necessary Snowflake Horizon policies and related governance capabilities to ensure agents are secure, auditable, and compliant with client and industry standards. • Lead the most complex, ambiguous Snowflake AI engagements from discovery through production, acting as the escalation point and “safety net” for critical Snowflake Intelligence accounts. • Develop phData‑wide blueprints, reference architectures, playbooks, guardrail templates, and ROI frameworks for Snowflake Intelligence–based agent deployments. • Mentor Consultants and Senior Consultants, modeling how to own projects end‑to‑end and effectively engage executive stakeholders, while evangelizing LCNC agentic patterns across the practice. • Partner with Sales and Solutions Engineering to scope complex AI Workforce opportunities, contribute to proposals, and help grow existing accounts by identifying “what’s next” for AI Workforce.

• Partner with senior and C‑Suite stakeholders to identify “agent‑first” opportunities across business units and define multi‑phase AI Workforce roadmaps tied to clear business outcomes • Lead the design of complex, production‑grade agentic systems using Snowflake Intelligence (no‑code/low‑code) and Cortex Search/Analyst, emphasizing configuration and semantic modeling over custom code • Design multi‑step “Reasoning & Acting” (ReAct) flows using Snowflake’s UI, semantic layers, and native apps to orchestrate tools, policies, and data workflows • Architect high‑accuracy retrieval‑augmented generation (RAG) and knowledge solutions using Cortex Search, with patterns for content onboarding, relevance tuning, evaluation, and continuous improvement • Advise on necessary Snowflake Horizon policies and related governance capabilities to ensure agents are secure, auditable, and compliant with client and industry standards • Lead the most complex, ambiguous Snowflake AI engagements from discovery through production, acting as the escalation point and “safety net” for critical Snowflake Intelligence accounts • Develop phData‑wide blueprints, reference architectures, playbooks, guardrail templates, and ROI frameworks for Snowflake Intelligence–based agent deployments • Mentor Consultants and Senior Consultants, modeling how to own projects end‑to‑end and effectively engage executive stakeholders, while evangelizing LCNC agentic patterns across the practice • Partner with Sales and Solutions Engineering to scope complex AI Workforce opportunities, contribute to proposals, and help grow existing accounts by identifying “what’s next” for AI Workforce.

• Design, build, and deploy AI agents using Microsoft Copilot Studio, aligned to real business processes and roles. • Translate manual or semi-structured business workflows into autonomous agents using low-code/no-code tools within the Microsoft ecosystem. • Implement agentic behaviors, including planning, tool use, contextual memory, and reflection, to deliver intelligent task execution. • Integrate Copilot solutions with enterprise systems such as Power BI, SharePoint, Outlook, and Teams. • Support internal teams in enablement, governance, lifecycle management, and safe experimentation with Copilot agents. • Develop and iterate on prompt templates, AI guardrails, fallback strategies, and continuous feedback loops to improve agent performance. • Partner with IT, data, and security teams to ensure responsible, governed, and scalable agent deployments. • Embed alongside client analytics and BI teams in a staff‑augmentation model, pairing on real Glean use cases while modeling best practices in semantic modeling, governance, and agent design. • Lead recurring enablement touchpoints (developer workshops, guided build sessions, office hours) to help client teams independently design, deploy, and iterate on Glean agents. • Co‑create reusable enablement assets (playbooks, labs, prompt libraries, “how‑to” guides) that client champions can use to scale training across business units.