AI Engineer

ClinDCast

  • Warren, Alabama
  • 30+ days ago

    Highlights

    As a result, there is a growing demand for a range of patient-centric services, including personalized care that is tailored to each individual's unique needs, health equity that ensures access to care for all, price transparency to make healthcare more affordable, streamlined prior authorizations for medications, the availability of therapeutic alternatives, health literacy to promote informed decision-making, reduced costs, and many other initiatives designed to improve the patient experience. Our suite of services is designed to cater to a broad range of needs of healthcare organizations, including healthcare IT innovation, electronic health record (EHR) implementation & optimizations, data conversion, regulatory and quality reporting, enterprise data analytics, FHIR interoperability strategy, payer-to-payer data exchange, and application programming interface (API) strategy.

    Numbers & Facts

    LocationWarren, Alabama

    Description

    Job Title: AI/ML Engineer – Generative AI & LLM
    Job Summary
    We are seeking a skilled AI/ML Engineer with expertise in Generative AI, Large Language Models (LLMs), and agent-based systems. The ideal candidate will design, develop, and deploy scalable AI solutions, leveraging modern frameworks and cloud-based MLOps practices to deliver production-grade systems. This role involves close collaboration with cross-functional teams to translate business requirements into intelligent, reliable AI applications.
    Key Responsibilities
    Generative AI & LLM Development
    •  Design, fine-tune, and deploy LLM-based solutions for enterprise use cases such as document intelligence, summarization, and conversational AI. 
    •  Build Retrieval-Augmented Generation (RAG) pipelines using vector databases to enhance response accuracy and contextual grounding. 
    •  Develop prompt engineering strategies and evaluation frameworks to ensure output quality, consistency, and safety. 
    •  Integrate LLMs with enterprise systems using frameworks like LangChain, LlamaIndex, or similar tools. 
    •  Evaluate and benchmark different foundation models to select optimal solutions for business needs. 
    AI Agents & Intelligent Automation
    •  Architect and implement AI agents capable of multi-step reasoning and task execution. 
    •  Develop agentic workflows using modern design patterns for complex, multi-turn interactions. 
    •  Implement human-in-the-loop mechanisms to ensure compliance, reliability, and risk control. 
    •  Integrate AI agents with APIs, enterprise platforms, and orchestration tools. 
    •  Establish guardrails, monitoring, and audit logging for responsible AI usage. 
    MLOps & Deployment
    •  Build and maintain end-to-end MLOps pipelines including training, validation, deployment, and monitoring. 
    •  Implement CI/CD pipelines for machine learning models to enable continuous delivery. 
    •  Deploy models as scalable APIs or batch services using cloud-native platforms. 
    •  Monitor model performance for drift, degradation, and anomalies in production. 
    •  Maintain model governance, versioning, and lineage tracking for auditability. 
    Collaboration & Delivery
    •  Work with business stakeholders to translate requirements into AI-driven solutions. 
    •  Participate in Agile/Scrum development processes and contribute to sprint deliverables. 
    •  Create technical documentation including solution designs, APIs, and operational guides. 
    •  Mentor junior team members and contribute to best practices in AI engineering.

    Flexible work from home options available.

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