Forward-deployed AI Engineer

Embed with SCAN’s teams as a forward-deployed AI Engineer to uncover measurable AI opportunities and deliver production-grade, AI-enabled systems.

Responsibilities

• Embed with SCAN’s teams to understand workflows, operational challenges, and strategic priorities
• Lead discovery activities, including stakeholder interviews, workflow observation, process analysis, and opportunity assessment
• Translate ambiguous business problems into technical requirements and measurable success criteria
• Build trusted relationships with SCAN leaders and act as a strategic technology partner
• Design, develop, test, deploy, and support AI-enabled applications using SCAN’s large language models (LLMs), AI agents, and retrieval-augmented generation (RAG)
• Apply workflow automation, APIs, and modern software engineering practices to deliver enterprise solutions
• Rapidly prototype solutions, validate concepts with users, and iterate based on business feedback
• Build production-ready software using SCAN’s enterprise AI platform, including reverse-integration of new capabilities to the core platform
• Evaluate emerging AI technologies and recommend approaches aligned to business needs
• Translate complex business problems into scalable and maintainable technical architectures
• Collaborate with architects, product managers, platform engineers, data engineers, and security teams to deliver enterprise AI solutions
• Develop reusable components, patterns, and technical assets to accelerate future AI development
• Contribute to engineering standards, best practices, and continuous improvement across the AI organization
• Define measurable success metrics for AI solutions and monitor business impact after deployment
• Continuously optimize solutions using operational data, user feedback, and changing business needs
• Identify additional automation and AI opportunities through ongoing engagement with business partners
• Support organizational adoption of AI through education, coaching, and change management
• Apply responsible AI practices, including transparency, traceability, explainability, fairness, privacy, and human oversight
• Partner with security, compliance, legal, and governance teams to support safe and appropriate AI use
• Document solution design, risks, controls, assumptions, and operational considerations for AI systems
• Ensure AI solutions comply with organizational standards, regulatory requirements, and security policies

Requirements

• Bachelor’s Degree or equivalent experience in Computer science, Engineering, or a related field
• Deep applied understanding of LLM-based architectures, RAG, vector embeddings, prompt engineering, and agent orchestration
• Experience designing, building, and deploying AI-enabled applications, services, workflows, and integrations
• Proficiency with Azure AI Services, Azure AI Foundry, and enterprise content management platforms (SharePoint, Microsoft 365, Teams, Confluence)
• Strong Python (or equivalent), REST APIs, ML/LLMOps tooling, and frameworks (FastAPI, LangChain, Microsoft Agent Framework, etc.)
• Ability to connect business requirements to technical solutions, build reusable components, and improve adoption and operational impact
• Collaborative communicator comfortable engaging non-technical stakeholders and cross-functional teams
• Curiosity, initiative, and continuous learning mindset; adapts quickly to new frameworks and technologies
• Leadership skills, including developing others
• Business insight, problem-solving ability, and a strategic mindset to create strategies that sustain competitive advantage
• Business partnering skills, self-direction, and influence; able to define roadmaps, persuade skeptics, and drive adoption of new processes or technologies

Technologies

• Python
• REST APIs
• FastAPI
• LangChain
• Microsoft Agent Framework
• Azure AI Services
• Azure AI Foundry
• SharePoint
• Microsoft 365
• Teams
• Confluence
• LLMs
• AI agents
• Retrieval-augmented generation (RAG)
• Vector embeddings
• Prompt engineering
• Agent orchestration
• ML/LLMOps tooling
• Enterprise AI platform

Experience

• 6+ years of experience (minimum requirement) in AI engineering, software engineering, data engineering, machine learning, automation, or enterprise technology delivery

Benefits

• Base salary range: $125,400 to $215,975 annually
• Annual employee bonus program
• Robust wellness program
• Generous paid-time-off (PTO)
• 11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
• Excellent 401(k) retirement saving plan with employer match
• Robust employee recognition program
• Tuition reimbursement
• Opportunity to contribute to a team supporting members and community

Preferred Certifications or Licenses

• Microsoft Certified: Azure AI Engineer Associate
• Relevant certifications in cloud platforms, AI engineering, machine learning, data engineering, or software development (beneficial)
• Additional certifications in Responsible AI, Data Governance, Cybersecurity, or Healthcare Informatics (advantageous)

Preferred Experience

• Extensive 6+ years in AI engineering, software engineering, data engineering, machine learning, automation, or enterprise technology delivery, ideally within regulated industries such as healthcare
• Hands-on experience (3+ years) building AI-enabled applications, integrating large language models, implementing RAG patterns, or delivering machine learning solutions
• Proven track record delivering enterprise-scale AI or digital transformation initiatives with cross-functional collaboration (business, healthcare, data, security, compliance, and technology)
• Experience building production-grade applications, APIs, data pipelines, automation workflows, or cloud-based AI services
• Familiarity with Azure AI Foundry, Azure OpenAI, Azure AI Services, Databricks, Snowflake, or similar enterprise AI and data platforms (highly valued)
• Strong stakeholder management and communication skills, translating business needs into scalable technical solutions and driving adoption across diverse teams
• Healthcare domain expertise, including regulatory and member-focused nuances (plus)

Location: Long Beach, CA (onsite)