Hybrid Senior AI Architect

at Inogen

• Job title: Senior AI Architect
• Job type: Full Time
• Experience level: Senior
• Salary: $140,000 - $145,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Azure, Cloud, Distributed Systems, IoT, Oracle, Python, ServiceNow
• Location requirements: Hybrid, Plano, United States

About the role

• Senior AI Architect at Inogen defining and leading enterprise AI architecture across predictive, generative, and agentic AI systems. Shaping AI capabilities within commercial and operational platforms.

Responsibilities

• Define the Enterprise AI Blueprint
• Establish and evolve the company’s AI reference architecture
• Set standards for how AI systems are built, deployed, governed, and monitored
• Design AI service layers that support both real-time and batch decisioning
• Ensure multi-region readiness including US, EU, and alignment with data residency requirements
• Act as the lead architect for AI initiatives across business domains
• Build Predictive & Real-Time Intelligence
• Architect predictive maintenance and IoT-driven data intelligence & anomaly detection systems
• Design event-driven AI workflows integrated into business operations
• Ensure sensitive data is encrypted, masked, and processed with consent-aware controls
• Embed explainability and monitoring into all deployed models
• Lead the Shift to Agentic AI
• Architect supervised AI agents capable of reasoning, invoking tools, and acting across systems
• Define guardrails, identity boundaries, escalation controls, and traceability
• Ensure AI agents operate efficiently, effectively, and safely across Salesforce, Brightree, Oracle, Five9, ServiceNow, and internal workflows
• Establish testing, red-teaming, and evaluation standards for agent behavior
• Evolving the Multi-Model Strategy
• Define how we leverage and govern multiple foundation models (OpenAI, Anthropic, and others)
• Design routing, fallback, and cost-aware inference strategies
• Implement RAG architectures with controlled retrieval and knowledge governance
• Introduce structured evaluation to measure hallucination, grounding, and reliability
• Prevent vendors lock-in through modular architecture
• Establish MLOps & LLMOps Discipline
• Define lifecycle governance from experimentation to production
• Implement model registry, CI/CD pipelines, monitoring, and rollback mechanisms
• Standardize feature management and drift detection
• Create traceable audit frameworks across AI systems
• Enable AI for Business functions, Products, & Services
• Enable AI-powered sales enablement, service automation, and customer intelligence
• Partner with business and R&D teams to embed intelligence into workflows, products and services
• Support secure data monetization initiatives and advanced analytics capabilities
• Embed Governance & Risk Management
• Align AI architecture with HIPAA, GDPR, EU AI Act considerations, and recognized AI risk frameworks
• Partner with Security, Legal, and Compliance to ensure AI systems are defensible
• Build cost governance mechanisms to ensure AI usage is economically sustainable.

Requirements

• Bachelor’s degree in computer science, Data Science, AI, or Mathematics (required)
• Master’s or Ph.D. in a relevant field is preferred
• 10+ years in enterprise architecture, distributed systems, or data platforms
• 5+ years delivering AI/ML systems in production environments
• Proven experience designing MLOps and LLMOps architectures
• Deep understanding of LLM systems, RAG patterns, and agentic AI frameworks
• Hands on experience, Python, Prompt Engineering, Reinforcement Learning
• Experience integrating AI across enterprise SaaS platforms
• Strong background in cloud-native architecture (Azure preferred)
• Familiarity with Snowflake, Dataiku, or similar data and AI platforms
• Experience operating in regulated or compliance-driven environments (medical device or healthcare preferred)
• Excellent collaboration skills, with the ability to work effectively with cross-functional teams, including product, engineering, and business stakeholders.
• Clear and effective communication skills, capable of explaining complex AI concepts to non-technical audiences.

Benefits

• health, dental, and vision insurance
• 401(k) plan plus employer contribution and match
• generous paid leaves such as vacation and sick leave
• paid volunteer time
• highly competitive and company-sponsored benefits
• wellbeing programs rooted in our strong culture of excellence.