Executive Director, Agentic Lab and Architecture Lead - Remote
Novartis
August 24, 2026
Remote
United States
IT
Responsibilities
- Define enterprise agentic AI technical architecture, reference patterns, and engineering standards aligned with approved platform, security, Responsible AI, and data governance.
- Establish reusable patterns for agent orchestration, memory, evaluation, observability, tool use, RAG, APIs, and enterprise system integration.
- Lead Agentic Lab innovation roadmap: rapid experimentation, technical validation, and controlled incubation of high-potential agentic AI technologies.
- Evaluate foundation models, agent frameworks, orchestration technologies, developer tooling, and emerging approaches for enterprise applicability.
- Build reusable proof-of-concepts, accelerators, architectural blueprints, and reference implementations to shorten time-to-value.
- Industrialize validated prototypes into production-ready enterprise capabilities; manage architecture readiness, technical documentation, risk assessment, and operating model handoff.
- Embed Responsible AI, security, privacy, accessibility, data governance, regulatory, and quality expectations; define evaluation/monitoring for reliability, explainability, performance, user safety, human oversight, and business value.
- Lead and coach technical talent; communicate technical direction, trade-offs, risks, and investment needs to senior stakeholders.
Qualifications
- Bachelor’s or advanced degree in Computer Science, AI, Engineering, or related.
- 12+ years designing enterprise software/AI architectures/data/AI products or cloud-native capabilities with executive-level technical leadership.
- Deep expertise in LLMs, agent frameworks, multi-agent orchestration, RAG, vector/graph DBs, tool/function calling, memory, evaluation, observability, APIs, event-driven patterns, and cloud-native deployment.
- Proven ability to create secure, scalable, governed enterprise reference architectures, standards, guardrails, and validated blueprints.
- Hands-on credibility with CI/CD, testing, release readiness, model/prompt evaluation, telemetry, cost/performance optimization, and operational support.
- Fluency in Responsible AI, security, privacy, data governance, access control, auditability, and compliance for regulated AI.
Preferred
- Experience in regulated environments (pharma/healthcare/life sciences/financial services).
- Familiarity with Azure AI Foundry/OpenAI, Semantic Kernel, Copilot Studio, LangChain/LangGraph, MCP/A2A, knowledge graphs/GraphRAG, and enterprise search.
Benefits
- Salary expected: $225,400–$418,600 (performance incentive; possible annual equity). Comprehensive US benefits and time off package.
- Define enterprise agentic AI technical architecture, reference patterns, and engineering standards aligned with approved platform, security, Responsible AI, and data governance.
- Establish reusable patterns for agent orchestration, memory, evaluation, observability, tool use, RAG, APIs, and enterprise system integration.
- Lead Agentic Lab innovation roadmap: rapid experimentation, technical validation, and controlled incubation of high-potential agentic AI technologies.
- Evaluate foundation models, agent frameworks, orchestration technologies, developer tooling, and emerging approaches for enterprise applicability.
- Build reusable proof-of-concepts, accelerators, architectural blueprints, and reference implementations to shorten time-to-value.
- Industrialize validated prototypes into production-ready enterprise capabilities; manage architecture readiness, technical documentation, risk assessment, and operating model handoff.
- Embed Responsible AI, security, privacy, accessibility, data governance, regulatory, and quality expectations; define evaluation/monitoring for reliability, explainability, performance, user safety, human oversight, and business value.
- Lead and coach technical talent; communicate technical direction, trade-offs, risks, and investment needs to senior stakeholders.
Qualifications
- Bachelor’s or advanced degree in Computer Science, AI, Engineering, or related.
- 12+ years designing enterprise software/AI architectures/data/AI products or cloud-native capabilities with executive-level technical leadership.
- Deep expertise in LLMs, agent frameworks, multi-agent orchestration, RAG, vector/graph DBs, tool/function calling, memory, evaluation, observability, APIs, event-driven patterns, and cloud-native deployment.
- Proven ability to create secure, scalable, governed enterprise reference architectures, standards, guardrails, and validated blueprints.
- Hands-on credibility with CI/CD, testing, release readiness, model/prompt evaluation, telemetry, cost/performance optimization, and operational support.
- Fluency in Responsible AI, security, privacy, data governance, access control, auditability, and compliance for regulated AI.
Preferred
- Experience in regulated environments (pharma/healthcare/life sciences/financial services).
- Familiarity with Azure AI Foundry/OpenAI, Semantic Kernel, Copilot Studio, LangChain/LangGraph, MCP/A2A, knowledge graphs/GraphRAG, and enterprise search.
Benefits
- Salary expected: $225,400–$418,600 (performance incentive; possible annual equity). Comprehensive US benefits and time off package.