
Enterprise AI Architect
The Enterprise AI Architect is a strategic, hands-on leader who partners with the IT, Product, and Business leaders to unlock enterprise value through AI. Serving as Lucid’s trusted authority on AI architecture, this role shapes the end-to-end strategy—from opportunity discovery and platform selection to model governance and production-scale delivery. The Enterprise AI Architect drives cross-functional alignment, embeds AI best practices into product, IT, and business roadmaps, and cultivates an innovation-forward culture that elevates skills, transparency, and measurable impact across the organization.
You Will:
Strategic Architecture & Governance
- Select, design, and implement AI capabilities across core Enterprise SaaS platforms—Salesforce (AgentForce), SAP S/4HANA & BTP (Joule, AI Core), ServiceNow (Now Assist), and Microsoft 365 Copilot—building chatbots, autonomous agents, and embedded predictive/generative apps that elevate CRM, ERP, collaboration, and ITSM workflows.
- Define the enterprise-wide AI reference architecture (LLMs, MLOps, vector DBs, RAG patterns, multimodal pipelines) that aligns Product, IT, and Business roadmaps.
- Own AI technology standards, guardrails, and design patterns—balancing innovation velocity with security, privacy, and ethical use (NIST RMF, ISO 42001, EU AI Act readiness).
- Define and maintain an enterprise-wide AI capability maturity model and staged adoption roadmap, setting clear gate criteria, ROI metrics, and compliance checkpoints so each domain (Product, IT, and Business) advances safely and predictably toward generative-AI at scale.
Delivery & Enablement
- Guide cross-functional teams in turning use-case backlogs into scalable AI services, proofs-of-concept, and production deployments.
- Establish MLOps foundations—CI/CD for models, feature stores, observability, and Responsible-AI evaluation pipelines.
- Partner with Security & Legal on model provenance, IP protection, and third-party-model risk assessments.
Value Realization & Evangelism
- Publish quarterly AI impact scorecards that translate technical metrics (e.g., precision, latency, cost-per-inference) into business KPIs, and actively broadcast successes and lessons learned across exec forums and all-hands to sustain momentum and surface new opportunities.
- Mentor domain architects and data scientists; run workshops that upskill engineers & business stakeholders on the art-of-the-possible.
You Bring:
- 10+ years in enterprise architecture or large-scale software engineering, with 5+ years designing and deploying AI/ML solutions (including generative AI/LLMs).
- Demonstrated success operationalizing AI in at least two domains (e.g., manufacturing optimization, intelligent automation, personalized digital experiences).
- Mastery of modern AI stack: Python, TensorFlow/PyTorch, model fine-tuning, vector search (Milvus/PGVector), orchestration frameworks (LangChain, LlamaIndex), and major cloud AI platforms (AWS Bedrock, Azure AI, GCP Vertex).
- Deep knowledge of data architecture (ELT into Snowflake, event streams, API/micro-service patterns) and integration tooling (Boomi, Kafka, REST/gRPC).
- Proven track record establishing governance over model lifecycle, data privacy (GDPR/CCPA), and AI ethics.
- Influential communicator comfortable translating technical vision into board-level business value.
- Bachelor’s in Computer Science, Data Engineering, or related;
- Bonus: Automotive or high-volume manufacturing experience; exposure to autonomous systems or embedded AI.
Base Pay Range (Annual)
$216,800 - $317,900 USD
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