AI Engineer​/Requisition

Brief Description

Hybrid:
Applicants must be a California resident as of their first day of employment.

We are seeking an experienced AI Engineer to design, build, and operate production-grade generative AI systems. You will work across retrieval-augmented generation (RAG), agentic workflows, unstructured data processing and AI-powered automation partnering closely with product, data and application teams to deliver real business impact. This role sits at the intersection of AI systems engineering and applied product development, with a strong emphasis on scalability, reliability and measurable outcomes.

• Strategize and define the roadmap for AI-driven solutions across the organization
• Lead technical discussions to translate business requirements into scalable AI architectures and system designs
• Experience with agent frameworks (e.g., Lang Graph, Auto Gen, CrewAI, or similar)
• Collaborate with cross-functional partners to integrate AI solutions into existing business workflows and decision-making processes
• Evaluate and select appropriate AI/ML technologies, platforms and frameworks to meet specific business needs
• Drive best practices in AI solution development and engineering
• Collaborate with business and technical stakeholders to translate existing challenges into AI-powered solutions
• Design and implement embedding pipelines, vector indexes and retrieval strategies for intelligent search and recommendation systems
• Build and maintain scalable, secure APIs and microservices that expose AI capabilities to internal and external applications
• Partner with application teams to:
• Improve retrieval accuracy through prompt engineering and grounding
• Optimize token usage and inference costs
• Enhance observability and evaluation pipelines
• Integrate real-time and virtualized data sources into AI workflows in collaboration with data engineering teams
• Monitor and refine models and pipelines to ensure accuracy, performance, reliability, and explainability
• Lead AI initiatives from ideation through production, ensuring alignment with business goals

• Design, develop, and operationalize Generative AI solutions leveraging Large Language Models (LLMs), including evaluation, Retrieval-Augmented Generation (RAG), fine-tuning and model observability.
• Apply Generative AI capabilities to enterprise business intelligence use cases enabling advanced analytics and decision support.
• Build and maintain scalable data solutions aligned with data engineering and data warehousing best practices.
• Design, develop and support production-grade distributed systems to ensure reliability, scalability and performance.
• Develop and maintain data pipelines and applications using Python, SQL and strong software engineering principles.
• Work with relational databases and modern data platforms to support analytical and operational workloads.
• Design and implement embedding-based search solutions, including integration with vector databases.
• Leverage cloud platforms (preferably Azure; AWS/GCP acceptable) to build and deploy data and AI solutions.
• Develop and maintain dashboards and reporting solutions using business intelligence tools.
• Drive end-to-end project execution from concept through delivery, in fast-paced and evolving environments.
• Operate effectively under ambiguity, demonstrating strong ownership, accountability and problem-solving skills.
• Collaborate cross-functionally with technical and business stakeholders to deliver impactful solutions.
• Continuously evaluate and adopt emerging technologies within the rapidly evolving AI/ML landscape.
• Domain knowledge including familiarity with healthcare concepts and regulatory considerations (preferred).

• Constant and close visual work at desk or computer.
• Constant sitting and working at desk.
• Constant data entry using keyboard and/or mouse.
• Frequent use of telephone headset.
• Constant verbal and written communication with staff and other business associates by telephone, correspondence, or in person.
• Frequent lifting of folders and other objects weighing between 0 and 30 lbs.
• Frequent walking and standing

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• Bachelor’s degree or equivalent work experience required.

• 4+ years of experience in AI/ML engineering, data engineering, or backend software engineering

• Experience working with unstructured data at scale
• Hands-on with Lang Chain, Llama Index, Langflow, n8n or similar orchestration tools
• Knowledge of Docker and Kubernetes
• Familiarity with data pipelines and ETL patterns
• Experience leading technical strategy and architectural decisions for data-intensive applications
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders. Design, develop, and operationalize Generative AI solutions…