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AI Engineer / Job Requisition 1023714309

Allameda Alliance for Health

Alameda, CA · HybridJobSeen todaySeen in employer's feed today

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At a glance

Compensation
No compensation found
Location
Alameda, CAHybrid
Work Authorization
Not specified

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Job overview

The AI Engineer designs, builds, and operates production-grade generative AI systems across retrieval-augmented generation, agentic workflows, unstructured data processing, and AI-powered automation. The role partners with product, data, application, business, and technical teams to deliver scalable, reliable solutions with measurable outcomes. It leads AI initiatives from ideation through production and applies generative AI to enterprise business intelligence, analytics, and decision support.

Skills & qualifications

RequiredNice to have

Skills

Generative AILarge Language ModelsRetrieval-Augmented GenerationFine-TuningModel ObservabilityEnterprise Business IntelligenceData EngineeringData WarehousingDistributed SystemsPythonSQLSoftware EngineeringRelational DatabasesAgent FrameworksLangGraphAutoGenCrewAIEmbedding PipelinesVector IndexesRetrieval StrategiesAPI DevelopmentMicroservicesPrompt EngineeringGroundingInference Cost OptimizationEvaluation PipelinesData Pipelines

Qualifications

California Residency at Start

Full job description

Hybrid : Applicants must be a California resident as of their first day of employment. PRINCIPAL RESPONSIBILITIES: 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. Principal responsibilities include: 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., LangGraph, AutoGen, 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: o Improve retrieval accuracy through prompt engineering and grounding o Optimize token usage and inference costs o 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 ESSENTIAL FUNCTIONS OF THE JOB 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. []{style="font "}

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