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Locus Robotics

Director, AI Enterprise Architect

Posted Yesterday
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Remote
Hiring Remotely in United States
175K-250K Annually
Senior level
Remote
Hiring Remotely in United States
175K-250K Annually
Senior level
The Director of AI Enterprise Architect will lead the company's AI transformation strategy, redesign workflows, and develop scalable AI systems across various enterprise functions.
The summary above was generated by AI

Locus Robotics is a global leader in Physical AI for warehouse automation. We are at an inflection point: AI is evolving from a productivity tool into the operating system that powers how we work and how our products deliver value. The Director, AI Enterprise Architect will make this transition real across the enterprise.

The Director, AI Enterprise Architect is a high-visibility, cross-functional leadership role with direct C-suite mandate. You will act as a force multiplier across the organization partnering with leaders to identify where AI creates the highest leverage, translating business requirements into scalable AI-native workflows, and building them. 

This is a rare opportunity to join one of the largest privately held robotics companies in the U.S. at the frontier of Physical AI, at a moment when enterprise-wide AI transformation is actively underway. This AI-first agenda has full CEO and board visibility. You will own the direction, execution, and impact.

This is both a strategy and build role—you will define the roadmap, architect the platform, and lead execution.

ResponsibilitiesEnterprise AI Transformation Strategy
  • Define and drive the company-wide AI roadmap, including prioritization frameworks, sequencing of initiatives, and executive alignment. Ensure a relentless focus on business outcomes rather than tool adoption.
AI-Native Workflow Redesign
  • Partner with leaders across Sales, Customer Success, Finance, Operations, and Marketing to identify high-leverage opportunities. Redesign processes from the ground up into AI-native, automated workflows.
AI Systems & Agentic Workflow Development
  • Design, build, and deploy production-grade AI systems, including agentic workflows that automate end-to-end processes. Own the full lifecycle—from scoping through deployment, monitoring, and iteration.
LLM & Data Integration Architecture
  • Architect scalable LLM-powered systems, including retrieval-augmented generation (RAG), unified context layers, and integration frameworks that connect enterprise data sources.
Data & Platform Engineering
  • Design and implement robust data pipelines, integration layers, and shared infrastructure that enable reusable, enterprise-wide AI capabilities. Ensure reliability, scalability, and accessibility across systems.
AI Governance, Security & Standards
  • Establish frameworks for model governance, risk management, data access, and security. Define standards for tools, evaluation, and responsible AI usage.
Technical Leadership & Culture Building
  • Drive AI adoption across the organization by mentoring leaders, establishing best practices, and fostering AI-native ways of working.
Core ExpertiseAdvanced AI & LLM Systems

Deep expertise in modern AI techniques, including transformer architectures, multimodal systems, and LLM application design. Strong understanding of:

  • Fine-tuning and adaptation (LoRA, PEFT, RLHF/DPO)
  • RAG systems, embeddings, and tokenization
  • Prompt engineering and tool-augmented agents
Production AI at Scale
  • Proven track record designing and operating production-grade AI systems that deliver measurable business impact (e.g., efficiency, revenue growth, cost reduction, user experience).
Enterprise Integration
  • Experience embedding AI into core enterprise systems (CRM, ERP, knowledge systems, collaboration platforms) to enable end-to-end workflow transformation.
Data & Platform Foundations

Strong grounding in:

  • Data engineering (ETL/ELT, pipelines, APIs)
  • Data architecture (Lakehouse, storage systems)
  • Metadata systems (catalogs, lineage)
  • Governance, security, and compliance frameworks
Scalable AI Platform Development

Experience building scalable AI platforms including:

  • Shared services, connectors, and agent frameworks
  • Evaluation and observability tooling
  • Deployment and scaling infrastructure
Hands-On Technical Leadership
  • Ability to operate at both strategic and deeply technical levels—prototyping, architecting, and delivering complex AI systems in production environments.
Communication & Influence
  • Exceptional ability to translate complex technical concepts into clear business value, align stakeholders, and drive execution across diverse teams.
Qualifications
  • 5+ years driving enterprise AI or digital transformation initiatives
  • 5+ years in software engineering, data engineering, or AI/ML roles
  • Strong proficiency in Python and modern cloud platforms (AWS, Azure, or GCP)
  • Hands-on experience with data engineering (ETL/ELT, APIs, lakehouse architectures, data quality frameworks) and platforms such as Databricks
  • Experience building and deploying production-grade agentic AI systems that take actions, not just generate outputs
  • Deep expertise in LLM integration, RAG pipelines, and enterprise AI tooling (e.g., GPT-4, Claude, or equivalent models)
  • Solid foundation in classical ML techniques (regression, classification, anomaly detection, time-series forecasting)
  • Strong business acumen with the ability to identify root problems and deliver practical, high-impact solutions
  • Excellent communication skills, with the ability to engage both technical teams and executive stakeholders

Additional Information 

Locus Robotics is an Equal Opportunity Employer.

The expected base salary range for this role is $175,000 - $250,000 annually, based on external market data, plus bonus and equity.  Actual offers will depend on factors such as the candidate’s experience, education, training, key or critical skills, geographic location, and current market and business conditions

Application Fraud Detection Notice: To help maintain a fair and secure hiring process, Locus Robotics may use AI-assisted and other automated tools to detect suspected fraud, misrepresentation, or misuse of the application process. Hiring decisions are not made solely by automated means unless otherwise disclosed where required by law



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