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About This Role
AI Solutions Engineer (ITS Architect III)
CalOptima
Join Us in this Amazing Opportunity
The Team You'll Join
We are a mission driven community-based organization that serves member health with excellence and dignity, respecting the value and needs of each person. If you are ready to advance your career while making a difference, we encourage you to review and apply today and help us build healthier communities for all.
More About the Opportunity
We are hoping you will join us as a AI Solutions Engineer (ITS Architect III) and help shape the future of healthcare where you'll be an integral part of our IT - Data Warehouse and Analytics Technology team, helping to strive for excellence while we serve our member health with dignity, respecting the value and needs of each of our members through collaboration with our providers, community partners and local stakeholders. This position has been approved to be Full Telework.
- If telework is approved, you are required to work within the State of California only and if Partial Telework, also come in to the Main Office in Orange, CA, at least two (2) days per week minimum.
The AI Solutions Engineer will serve as the primary technical resource for the organization's Enterprise AI Program, taking approved use cases from concept to production deployment. Following a build-and-buy approach, you will configure and extend vendor and embedded AI capabilities and develop targeted internal solutions where appropriate. For internal builds, you primarily leverages the Microsoft AI ecosystem (Copilot Studio, Azure AI, and Power Automate), grounding solutions in governed data from the organization's cloud-native enterprise data platform. Partnering closely with the AI Solutions Analyst, the incumbent will own technical build, deployment, and production reliability. You will also contribute to the program's shared AI platform foundation by building reusable components, integration patterns, and engineering standards that let the program scale. Partnering with Enterprise Architecture as a technical collaborator and with Cybersecurity, the AI Solutions Engineer will keep solutions within enterprise security and data-governance boundaries. Together, we are building a stronger, more equitable health system.
Your Contributions To the Team:
- 90% - Technical Responsibilities + Participates in a mission driven culture of high-quality performance, with a member focus on customer service, consistency, dignity and accountability. + Assists the team in carrying out departmental responsibilities and collaborates with others to support short- and long-term goals and priorities for the department. + Implements and configures vendor AI and automation platforms from procurement through production deployment, including provisioning, integration, testing, and handoff to operational teams. + Builds AI agents and workflows using Microsoft-native tooling such as Copilot Studio, uses Power Automate for operational handoffs and triggers, and writes pro-code integrations (Python, REST APIs, JSON) where robust custom logic is required. • Develops and deploys solutions using Azure AI Document Intelligence to extract, classify, and process structured and unstructured clinical and administrative documents. + Connects AI platforms and Microsoft tools to operational applications and governed enterprise data, partnering with Data Engineering for source pipelines rather than building them. + Develops and maintains prompt engineering workflows, agent logic, and retrieval-augmented generation (RAG) pipelines using Azure OpenAI Service and related Azure AI Services, grounding AI agents in governed enterprise data. + Builds and maintains the program's shared AI platform foundation and engineering standards, including reusable components, integration patterns, and consistent practices for agent design, security, and deployment. + Supports proof-of-concept development for internally built AI solutions, evaluating feasibility, documenting findings, and translating successful POCs into production-ready implementations with defined go/no-go criteria. + Partners with the AI Solutions Analyst on user acceptance testing and quality assurance, focusing on technical deployment and production readiness. + Owns the operational lifecycle of deployed AI solutions, monitoring performance and output quality, detecting changes in model behavior and prompt or retrieval-quality degradation, managing versions, and leading incident response. + Partners with Enterprise Architecture as a technical collaborator on complex builds, keeping solutions aligned with the organization's platform strategy and architectural standards. + Partners with Cybersecurity from use case intake through production deployment, designing AI workflows that keep member data within approved enterprise boundaries and applicable vendor agreements. + Supports build-vs-buy evaluations during use case discovery, providing technical perspective on feasibility, implementation complexity, integration requirements, and total cost of ownership. + Documents solution implementations for governance, audit readiness, and long-term maintainability, including integration maps, configuration details, and deployment runbooks. + Stays informed on emerging Microsoft AI capabilities, cloud-native AI engineering practices, and healthcare AI patterns, proactively recommending enhancements to the program's technical delivery approach. + Manages multiple implementation workstreams simultaneously, ensuring timely delivery and alignment with stakeholder expectations.
10% - Other Completes other projects and duties as assigned.
- +
Do You Have What the Role Requires?
- Bachelor's degree in computer science, information systems, software engineering, or a related field, plus 5 years of professional experience in technical implementation, software development, or AI and automation platform deployment required; an equivalent combination of education and experience sufficient to successfully perform the essential duties of the position such as those listed above may also be qualifying.
- 2 years of hands-on experience building, deploying, or integrating AI or large language model solutions in a production environment required.
You'll Stand Out More If You Possess the Following:
- Demonstrated experience building AI agents, automation workflows, or LLM-based solutions using Microsoft-native tooling including Copilot Studio, Power Automate, Azure AI Document Intelligence, or Azure AI Foundry.
- Experience with Azure OpenAI Service including prompt engineering, RAG pipeline design, and grounding LLM solutions in enterprise data.
- Experience with intelligent automation in an enterprise environment.
- Healthcare payer domain knowledge including familiarity with claims, eligibility, prior authorization, or care management data and workflows.
- Experience working within a government cloud or other highly regulated cloud environment with strict data governance, compliance, and security requirements.
- Exposure to cloud-native enterprise data platforms and their native AI capabilities (e.g., Snowflake Cortex, Microsoft Fabric, Databricks Mosaic AI).
- Familiarity with Microsoft 365 Copilot and the broader Microsoft AI ecosystem as it applies to enterprise productivity and workflow automation.
What the Regulatory Agencies Need You to Possess?
- N/A
Your Knowledge & Abilities to Bring to this Role:
- Develop rapport and establish and maintain effective working relationships with CalOptima Health's leadership and staff and external contacts at all levels and with diverse backgrounds.
- Work independently and exercise sound judgment.
- Communicate clearly and concisely, both orally and in writing.
- Work a flexible schedule; available to participate in evening and weekend events.
- Organize, be analytical, problem-solve and possess project management skills.
- Work in a fast-paced environment and in an efficient manner.
- Manage multiple projects and identify opportunities for internal and external collaboration.
- Motivate and lead multi-program teams and external committees/coalitions.
- Utilize computer and appropriate software (e.g., Microsoft Office: Word, Outlook, Excel, PowerPoint) and job specific applications/systems to produce correspondence, charts, spreadsheets, and/or other information applicable to the position assignment.
Your Physical Requirements (With or Without Accommodations):
- Ability to visually read information from computer screens, forms and other printed materials and information.
- Ability to speak (enunciate) clearly in conversation and general communication.
- Hearing ability for verbal communication/conversation/responses via telephone, telephone systems, and face-to-face interactions.
- Manual dexterity for typing, writing, standing and reaching, flexibility, body movement for bending, crouching, walking, kneeling and prolonged sitting.
- Lifting and moving objects, patients and/or equipment 10 to 25 pounds
Ways We Are Here For You
- You'll enjoy competitive compensation for this role. + Our current hiring range is: Pay Grade: 316 - $120,881 - $193,410 ($58.12 - $92.9856).
- The final salary offered will be based on education, job-related knowledge and experience, skills relevant to the role and internal equity among other factors.
- This position is approved for Full Telework (If the position is Telework, it is eligible in California only)
- A comprehensive benefits package
- CalPERS pension program and additional retirement packages.
- Additional benefits and perks including: + A generous PTO program + A quality work life balance + Various wellness programs + Tuition Reimbursement + Professional development opportunities + Career development opportunities + Flexible scheduling + And the satisfaction of knowing your work directly impacts and improves healthcare access for thousands of individuals and families.
Our Work Environment:
If located at the 500, 505 Building or a remote work location:
- Work is typically indoors and sedentary and is subject to schedule changes and/or variable work hours, with travel as needed.
- There are no harmful environmental conditions present for this job.
- The noise level in this work environment is usually moderate.
If located at PACE:
- Work is typically indoors in a clinical setting serving the frail and elderly.
- There may be harmful or hazardous environmental conditions present for this job.
- The noise level in this work environment is usually moderate to loud.
If located in the Community:
- Work is typically indoors and sedentary and is subject to schedule changes and/or variable work hours, with travel as needed.
- Employee will occasionally work outdoors in varied temperatures.
- There may be harmful or hazardous environmental conditions present for this job.
- The noise level in this work environment is usually moderate to loud.
Why Join Us?
We believe that diverse perspectives drive innovation. Each employee brings a unique perspective to the overall team and we value everyone's input and we are committed to creating an inclusive environment where you and every team member can thrive while making a meaningful impacts on our community members. Our team reflects and represents the communities we serve, and we welcome candidates from all backgrounds who share our commitment to accessible, quality healthcare.
What's Your Next Step?
All Applications will be accepted on a continuous basis until a sufficient number of qualified applications have been received. Do NOT miss out. If you want to join our team, the deadline for the first review of applications is October 28, 2026 at 9:00 PM (PST). We are encouraging you to apply early. If you apply after the first review date, your application is not guaranteed to be considered for this recruitment. This recruitment may close at any time without notice after the first review date.
Our Commitment to You
Your application and resume will be reviewed by a dedicated recruiter to this position. If your experience matches what we need, we will reach out to you to discuss the next steps. The selection process may include, but is not limited to, a skills assessment, phone screen and interview.
If you make it through the steps above and are selected for this exciting role, you will be required to undergo a reference and a background check (to include a conviction record) and if applicable also pass a drug screening and/or a post-offer pre-employment medical examination (for specific positions) If you are an Internal CalOptima Health applicant, please apply through the internal portal on InfoNet.
We will make sure to keep you updated through each step of the process on your candidate portal. Please make sure to watch for updates on your candidate portal and you emails which will be sent to the email address you listed on your application. Please check your email, including your SPAM folder, regularly throughout the recruitment process.
CalOptima Health is an equal opportunity employer and makes all employment decisions on the basis of merit. CalOptima Health wants to have qualified employees in every job position. CalOptima Health prohibits unlawful discrimination against any employee, or applicant for employment, based on race, religion/religious creed, color, national origin, ancestry, mental or physical disability, medical condition, genetic information, marital status, sex, sex stereotype, gender, gender identity, gender expression, transitioning status, age, sexual orientation, immigration status, military status as a disabled veteran, or veteran of the Vietnam era, or any other consideration made unlawful by federal, state, or local laws. CalOptima Health also prohibits unlawful discrimination based on the perception that anyone has any of those characteristics or is associated with a person who has, or is perceived as having, any of those characteristics.
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation at (714) 246-8400 if you are unable or limited in your ability to access job openings or apply for a job on this site as a result of your disability.
To apply, please visit: https://jobs.caloptima.org/jobs/ai-solutions-engineer-its-architect-iii-505-city-parkway-west-california-united-states
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Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Caloptima, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Caloptima AI Hiring
Caloptima has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Orange, CA, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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