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AI Engineer

Career Insights for Generative Artificial Intelligence Engineer

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What they do

A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.

$136,061 / year median in Colorado

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Job Description

Designs, builds, deploys, and leads enterprise generative AI solutions, including LLM applications, chatbots, copilots, RAG pipelines, and automation assistants. Integrates AI with Azure, Databricks, EHR, FHIR, and HL7 data while meeting HIPAA, PHI, and governance requirements. Develops data pipelines, evaluates and fine-tunes models, guides architecture decisions, conducts code reviews, mentors team members, and collaborates with clinical, operational, data, and product stakeholders. The summary above was generated by AI It's fun to work in a company where people truly BELIEVE in what they're doing! We're committed to bringing passion and customer focus to the business. Applicants must be authorized to work in the United States without the need for current or future visa sponsorship. Position Summary The AI Engineer III is a senior-level engineering role responsible for designing, building, and deploying enterprise AI solutions that enhance clinical, operational, and administrative workflows across Alpine Physician Partners. This individual will lead development of Generative AI applications—including LLM-powered chatbots, copilots, RAG pipelines, and automation assistants—integrated with Alpine's cloud infrastructure (Azure, Databricks) and healthcare data assets (EHR, FHIR, HL7). The AI Engineer III will contribute to Alpine's Enterprise AI Tech Foundation, ensuring solutions meet HIPAA, PHI, and data governance standards. Essential Functions AI Solution Development Design, implement, and fine-tune Generative AI applications including LLMs, RAG pipelines, and prompt engineering solutions for clinical and operational use cases. Build and maintain LLM-integrated microservices using frameworks such as LangChain, LlamaIndex, and OpenAI SDKs. Develop retrieval-augmented generation (RAG) architectures leveraging internal knowledge bases, EHR data, and structured clinical documents. Implement chatbots, copilots, and automation assistants for internal operations and clinical support. Evaluate and select foundation models (OpenAI, Anthropic, Azure OpenAI, Mistral) appropriate to use-case requirements. System Integration & Deployment Integrate AI solutions into enterprise systems using REST APIs, Azure services, and Databricks Data Intelligence Platform. Deploy scalable, production-grade AI services on Azure Cloud and Databricks Generative AI Stack. Build and maintain data pipelines supporting AI model ingestion, evaluation, and fine-tuning workflows. Partner with IT and business stakeholders to ensure all solutions comply with HIPAA, PHI, and Alpine data governance standards. Technical Leadership & Collaboration Serve as a subject matter expert for Generative AI, guiding team members on architecture decisions, best practices, and emerging LLM capabilities. Collaborate cross-functionally with clinicians, operations leaders, data teams, and product owners to translate business needs into AI-powered solutions. Conduct code reviews and establish coding standards for AI/ML development work. Contribute to the design and continuous improvement of Alpine's Enterprise AI Tech Foundation. Stay current with foundation model capabilities, open-source frameworks, and healthcare AI regulations. Participate in Agile/Scrum ceremonies including sprint planning, standups, and retrospectives. Adhere to Alpine's Compliance Program and all applicable federal and state laws and regulations. Other duties as assigned. Qualifications Education Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field; equivalent work experience considered. Experience Minimum 3-6 years of experience in AI/ML engineering or applied data science, with at least 1-2 years focused on Generative AI development. Minimum 6 years of experience required in creating robust enterprise-grade data engineering pipelines using SQL, Python, Apache Spark, ETL, ELT, Databricks Technology Stack, Azure Cloud Services, Cloud-based Data and Analytics platforms required. 8-10 years preferred. Minimum 3 years of experience required in cloud solution design blueprinting towards delivery of robust enterprise-grade solutions. Strong proficiency in SQL and data analysis required. Demonstrated experience building and deploying LLM-powered applications in a production environment. Experience working with healthcare data (EHR, FHIR, HL7) and regulated data environments strongly preferred. Experience in an Agile/Scrum software development environment. Required Technical Skills Proficiency in Python and frameworks including Databricks, LangChain, LlamaIndex, FastAPI, and Flask. Hands-on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI, Mistral) and embedding-based retrieval systems. Familiarity with vector databases such as Pinecone, FAISS, Chroma, and Weaviate. Knowledge of prompt engineering, RAG architecture design, model evaluation, and fine-tuning techniques. Cloud experience with Azure Cloud, Databricks Data Intelligence Platform, and the Azure Generative AI Stack. Proficiency in data pipelines, ETL processes, and API integration patterns. Preferred Technical Skills Experience with healthcare data standards (FHIR, HL7, EHR integration). Understanding of HIPAA compliance and PHI security best practices. Experience with MLOps tooling including MLflow, Kubeflow, and Airflow. Familiarity with model evaluation frameworks and prompt testing methodologies. Experience with Microsoft 365, Azure Active Directory, and enterprise security patterns. Knowledge, Skills & Abilities Strong analytical and problem-solving skills with the ability to work independently and drive ambiguous problems to resolution. Excellent verbal and written communication skills; able to explain complex AI concepts to non-technical stakeholders. Ability to mentor junior team members and provide technical guidance. Strong collaboration and cross-functional teamwork skills. Self-motivated, self-managed, and able to prioritize competing demands in a fast-paced environment. Proficient in Microsoft Office Suite.

Salary Range:

$150,000-$170,000 If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! Read Full Description Alpine Physician Partners Aurora, Colorado, USA Office Aurora, CO, United States Alpine Physician Partners Denver, Colorado, USA Office Denver, CO, United States Similar Jobs True Anomaly Machine Learning Engineer 2 Days Ago In-Office Denver, CO, USA 125K-220K Annually Mid level 125K-220K Annually Mid level Aerospace

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AI Atomic Red Team Caldera Ci/Cd Cloud Security Cobalt Strike Crowdstrike Entra Id Infrastructure-As-Code Llms Machine Learning Microsoft Defender Microsoft Sentinel Mitre Att&Ck Policy-As-Code Python SIEM Soar Splunk Tines Xdr What you need to know about the Colorado Tech Scene With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech Number of Tech Workers:

260,000; 8.5% of overall workforce (2024 CompTIA survey)

Major Tech Employers:

Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3

Key Industries:

Software , artificial intelligence , aerospace , e-commerce , fintech , healthtech

Funding Landscape:

$4.9 billion in VC funding in 2024 (Pitchbook)

Notable Investors:
Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures Research Centers and Universities:

Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute