Designs, deploys, and supports scalable AI/ML solutions, including predictive models, large language model applications, agentic workflows, and RAG pipelines. Builds production-grade MLOps and DevOps practices covering CI/CD, versioning, testing, monitoring, retraining, and rollback. Manages cloud deployments, observability, security, governance, HIPAA-aligned data practices, API integrations, documentation, and troubleshooting across data, infrastructure, model, and orchestration layers.
Primary City/State:
Virtual ArizonaCategory:
Data IntelligenceShift:
DayDepartment:
Augmented IntelligenceHours: Monday-Friday Days
Location: Remote -- Must be located in Arizona -- Occasional on site as needed.
Great care starts with great people. (Like you.)
At HonorHealth, you’ll find something special. From humble beginnings in 1927 to one of Arizona’s largest nonprofit healthcare systems, our culture is built on warmth and neighborly kindness. Behind every smile is a highly skilled professional with deep expertise and an unwavering dedication to what matters most — caring for the health and well-being of people and communities across the greater Phoenix area.
Responsibilities:
JOB SUMMARY
The Senior AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth. This role operationalizes models and pipelines, monitors performance, and partners with data, engineering, and stakeholders to deliver reliable solutions aligned to governance and data handling expectations. The role partners closely with data engineers, data scientists, platform teams, and business stakeholders to translate complex needs into production-ready deployments, monitor ongoing performance, and continuously improve AI/ML capabilities aligned to governance and operational standards.
ESSENTIAL FUNCTIONS
- Leads the design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives.
- Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management.
- Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
- Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
- Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency. Works with AI development team to a continuous improvement feedback loop.
- Ensures AI/ML and agentic solutions comply with data governance, privacy, security, and responsible AI expectations, including HIPAA-aligned practices where applicable.
- Creates and maintains technical documentation for architectures, models, workflows, operational procedures, assumptions, limitations, and support processes.
- Troubleshoots complex pipeline, infrastructure, model, and integration issues; implements fixes and drives continuous improvement in operational stability and delivery efficiency.
- Core Skills: Hands-on experience with cloud-native AI/ML services and infrastructure, preferably in Google Cloud Platform (GCP), including services for training, inference, orchestration, and scalable compute
- Proficiency info MLOps, DevOps, and software engineering practices such as CI/CD, Git-based workflows, containerization, Infrastructure as Code, and automated testing
- Proficiency with establishing connections via API calls and MCP servers.
- Strong SQL and data engineering skills with experience in large-scale data processing, backend engineering, and integration across enterprise data platforms
- Experience with API development and systems integration to embed AI/ML capabilities into enterprise applications and workflows
- Strong analytical and problem-solving skills with the ability to diagnose issues across data, models, infrastructure, and orchestration layers
- Excellent communication and collaboration skills with the ability to document and explain technical concepts clearly to both technical and non-technical stakeholders
- Performs other duties as assigned.
EDUCATION
- Bachelors Computer Science, Data Science, Engineering, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related quantitative field; or 4 years’ relevant experience Required
EXPERIENCE
- 7 years, of progressive experience in DevOps within a Cloud deployment in, AI/ML Ops, data engineering, or related software engineering roles, including at least 3 years deploying and operating AI/ML production workloads. Required
LICENSE AND CERTIFICATIONS
We're all in for your career.
Similar Jobs
Blockchain • Fintech • Payments • Financial Services • Cryptocurrency • Web3
Leads business development for USDC adoption across repo, derivatives, and dealer balance-sheet workflows. Engages swap dealers, primary dealers, FCMs, CCPs, custodians, and market infrastructure providers; drives pilots from design through execution; coordinates with product and engineering teams; aligns integrations with regulatory, legal, compliance, and risk requirements; advises leadership on capital and liquidity benefits; and negotiates strategic C-level partnerships.
Top Skills:
Apple MacosBlockchainChatgptGeminiGenerative AiGoogle SuiteSlackUsdc
Machine Learning • Payments • Security • Software • Financial Services
Supports Asset Management Group product strategies, policies, procedures, and processes; provides solutions for exceptional client experiences; handles escalated fiduciary, compliance, and operational matters; monitors risk and escalated issues; participates in enterprise initiatives; and serves as backup to the AMG Product Specialist Advisor. The role requires knowledge of trust and fiduciary services, retirement and tax planning, IRA administration, financial-services regulations, and client relationship management.
Top Skills:
Excel
Marketing Tech • Social Media • Software • Analytics • Business Intelligence
Manage a book of ~60 enterprise customers to drive adoption, retention, and expansion of Sprout's social media platform. Build executive relationships, run success cadences (MBRs, EBRs), surface risks, collaborate on renewals, and use data and generative AI tools to create ROI narratives and accelerate work. Partner with onboarding, professional services, and renewals to meet retention and growth KPIs.
Top Skills:
ClaudeGoogle SuiteGainsightGeminiSalesforceSprout SocialTableau
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
