AI Engineer

AdventHealth; Town of Florida (NY); On-site; USD 96,000 - 179,000; Full time

Benefits offered by this job

Benefits from Day One

Paid Time Off from Day One

403-B Retirement Plan

4 Weeks Parental Leave

Career Development

Whole Person Well-being Resources

Mental Health Resources and Support

Pet Benefits

Job summary

AdventHealth is seeking an AI/ML Engineer to design and implement end-to-end LLM workflows, including prompt engineering, model fine-tuning, and RAG for healthcare-scale applications. You will own the full lifecycle from experimentation to deployment, with CI/CD, Docker/Kubernetes, and cloud-native architectures.

You will collaborate with data scientists, DevOps, and engineers to deliver secure, observable AI services, aligned with HIPAA and organizational governance.

Qualifications

• Strong experience with transformer-based architectures and LLM customization.
• Proficiency in Python, ML frameworks, and model management libraries.
• Expertise in deploying ML models into production using CI/CD, Docker, Kubernetes.
• Knowledge of vector databases and RAG pipelines for enterprise search.
• Experience with MLflow, Weights & Biases, SageMaker, or Azure ML.
• Understanding of data pipelines and feature store integration.
• Ability to balance performance, cost, latency, and explainability.
• Excellent written and verbal communication for technical and non-technical audiences.
• Experience deploying LLMs in enterprise or regulated environments is preferred.

Responsibilities

• Design and implement custom LLM workflows including prompt engineering and RAG.
• Own full lifecycle of AI models from experimentation to deployment and monitoring.
• Build scalable AI/ML infrastructure with model registries and vector stores.
• Evaluate and deploy foundation models into production with trade-off analysis.
• Architect cloud-native ML systems using Azure ML, AWS SageMaker, or Vertex AI.
• Containerize and deploy models with Docker and Kubernetes.
• Integrate AI models into applications via APIs and microservices.
• Implement IaC with Terraform and IaC tooling like Bicep.
• Ensure security, compliance, and observability of AI workflows.

Skills

Transformer architectures

Python

CI/CD pipelines

Docker

Kubernetes

Cloud services

Vector databases

MLOps platforms

ETL/ELT

Explainability

Education

Bachelor’s degree

Master’s degree

Tools

Terraform

Bicep

LangChain

OpenLLM

DeepSpeed

Job description

Our Promise To You

Joining AdventHealth is about being part of something bigger. It’s about belonging to a community that believes in the wholeness of each person, and serves to uplift others in body, mind and spirit. AdventHealth is a place where you can thrive professionally, and grow spiritually, by Extending the Healing Ministry of Christ. Where you will be valued for who you are and the unique experiences you bring to our purpose-minded team. All while understanding that together we are even better.

All the benefits and perks you need for you and your family:

• Benefits from Day One: Medical, Dental, Vision Insurance, Life Insurance, Disability Insurance
• Paid Time Off from Day One
• 403-B Retirement Plan
• 4 Weeks 100% Paid Parental Leave
• Career Development
• Whole Person Well-being Resources
• Mental Health Resources and Support
• Pet Benefits

Schedule

Full time

Shift

Day (United States of America)

Address

902 INSPIRATION AVE

City

ALTAMONTE SPRINGS

State

Florida

Postal Code

32714

Job Description

Design and implement custom LLM workflows including prompt engineering, model fine-tuning, instruction tuning, and retrieval-augmented generation (RAG) to meet enterprise-specific requirements. Own the full lifecycle of AI models from experimentation to deployment, monitoring, versioning, and continuous improvement using industry-standard MLOps practices. Design and develop comprehensive technical plans and system architectures that effectively address identified problems and proposed AI-driven solutions, ensuring scalability, maintainability, and alignment with organizational objectives. Build and maintain scalable AI/ML infrastructure including model registries, vector databases, embedding stores, experiment tracking tools, and inference pipelines. Evaluate, integrate, and deploy foundation models (commercial and open-source) into production environments with clear performance, cost, and privacy tradeoff analysis. Architect and implement cloud-native ML systems using platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI; containerize and deploy models using tools like Docker, Kubernetes, or serverless frameworks. Work closely with data scientists, DevOps, software engineers, and business stakeholders to integrate AI models into existing applications and services with reliable APIs and monitoring. Design and develop secure, scalable middleware solutions and APIs to integrate enterprise systems with large language models and AI services. Leverage cloud-native technologies to enable seamless orchestration of data and model workflows across distributed environments. Implement cloud infrastructure using Infrastructure-as-Code (IaC) principles with tools such as Terraform and Bicep. Automate deployment of secure, compliant, and cost-optimized cloud resources to support AI model serving, vector stores, and data pipelines. Enforce enterprise-grade security protocols across AI workflows, including access control, secret management, and policy-as-code. Ensure compliance with organizational and regulatory standards when integrating AI capabilities into production systems Establish observability frameworks to monitor latency, throughput, drift, accuracy, and resource consumption. Continuously optimize models for performance, efficiency, and user impact. Ensure models comply with ethical AI principles, data privacy regulations, and organizational governance frameworks. Document model behavior, limitations, and evaluation benchmarks. Stays up to date with advancements in AI algorithms, frameworks, natural language processing (NLP), and large language models (LLMs) to recommend innovative solutions.

Knowledge, Skills, And Abilities

• Strong experience with transformer-based architectures (e.g., GPT, LLaMA, Mistral, Claude) and LLM customization techniques (LoRA, PEFT, instruction tuning, prompt chaining).[Required]
• Proficiency in Python, ML frameworks (e.g., PyTorch, TensorFlow), and model management libraries (e.g., Hugging Face Transformers, LangChain, OpenLLM).[Required]
• Expertise in deploying ML models into production using CI/CD pipelines, Docker, Kubernetes, and cloud services (Azure, AWS, or GCP).[Required]
• Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines for enterprise search and contextualization.[Required]
• Experience with MLOps platforms like MLflow, Weights & Biases, SageMaker, or Azure ML for experiment tracking and model lifecycle orchestration.[Required]
• Understanding of data pipelines, ETL/ELT practices, and feature store integration in AI systems.[Required]
• Ability to evaluate trade-offs between performance, cost, latency, and explainability in real-world AI systems.[Required]
• Excellent written and verbal communication skills with the ability to document systems and present findings to technical and non-technical audiences.[Required]
• Ability to quickly learn, experiment, and iterate on AI-driven strategies. [Required]
• Experience deploying LLMs in enterprise or regulated environments (e.g., healthcare, finance, government). [Preferred]
• Familiarity with open-weight foundation models and fine-tuning at scale using distributed training frameworks (e.g., DeepSpeed, FSDP, Ray). [Preferred]
• Knowledge of responsible AI toolkits (e.g., IBM AIF360, Fairlearn, Explainable AI tools) and compliance frameworks (HIPAA, GDPR).[Preferred]
• Experience integrating AI models into user-facing applications via APIs, SDKs, or microservices.[Preferred]

Education

• Bachelor’s [Required]
• Master’s [Preferred]

Field Of Study

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Master’s degree in Computer Science, Information Technology, Data Science, or a related field.

Work Experience

• 5+years of experience in machine learning or AI engineering roles, including direct involvement with model development, deployment, or integration into production systems. [Required]
• Hands-on experience developing, fine-tuning, or integrating LLMs (e.g., OpenAI GPT, LLaMA, Mistral, Claude, Cohere) in applied setting .[Required]
• Experience with cloud-based platforms with a strong emphasis on AI/ML services(e.g., Azure ML, AWS SageMaker, GCP Vertex AI).[Required]
• 1+ years of experience working with LLM orchestration tools (e.g., LangChain, Semantic Kernel, AutoGen, CrewAI).[Preferred]
• Experience with vector databases and building RAG pipelines for contextual AI use cases.[Preferred]
• Experience in regulated industries (e.g., healthcare, finance) with an understanding of privacy, compliance, and ethical AI implementation.[Preferred]
• Certification in AI automation tools, or cloud-based AI services.[Preferred]

Physical Requirements:

(Please click the link below to view work requirements) Physical Requirements – https://tinyurl.com/23km2677

Pay Range

$96,266.14 - $179,045.63

Background Screening Requirement (Florida Law)

Certain positions are subject to Florida Level 2 background screening , including fingerprinting, as required by state law.

Applicants may review general information about Florida’s background screening requirements at the Florida Care Provider Background Screening Clearinghouse :

https://info.flclearinghouse.com/

This facility is an equal opportunity employer and complies with federal, state and local anti-discrimination laws, regulations and ordinances.