Senior AI Architect
Description
Job Summary
We are looking for a hands-on senior AI architect who will define how AI operates across our enterprise — not only to architect individual projects, but as a governed, scalable capability embedded into the way we work. Reporting to the VP, Chief Data and Information Officer, this role will shape and lead our enterprise AI architecture across predictive models, generative AI, and agentic AI systems. You will design the foundation that allows AI to be safely embedded into our commercial, operational, enterprise, and digital platforms — while remaining secure, compliant, cost-disciplined, and aligned to pragmatic and measurable business outcomes.
Responsibilities (Specific tasks, duties, essential functions of the job)
- 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.
Qualifications (Experience and Education)
- 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.
Disclaimer
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified.
Inogen assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $120,000.00 and $145,000.00 annually. However, actual base salary if hired will be determined on an individualized basis and will be based on non-discriminatory factors, including as to individual skills, education, experience and market location.
Our Benefits and Rewards:
In addition to the expected base salary, this role is eligible to participate in Inogen’s annual performance bonus incentive plan, highly competitive and company-sponsored benefits, and wellbeing programs rooted in our strong culture of excellence. As a valued member of our team, Inogen provides health, dental, and vision insurance, 401(k) plan plus employer contribution and match, and generous paid leaves such as vacation and sick leave, including paid volunteer time, that can support you and your family through moments that matter.
Inogen is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.