Description review

Enterprise AI Architect

Alternate Solutions Health Network · United States · back to the listing

HR standards

24/100

poor

Title ↔ description

72/100

solid

Reads as

Machine Learning Engineer

92% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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What the listing never says

  • 27 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

The listing, marked up

Our culture and people are what set us apart from other post-acute care providers. We’re dedicated to the growth and development of our team to set them up for success. We CARE for our patients like they are our own FAMILY.

SUMMARY

Alternate Solutions is looking for an Enterprise AI Architect to work closely with Business Stakeholders, Leadership and Technical teams to design and develop Artificial Intelligence / Machine Learning powered highly scalable and performant mobile and web applications. The ideal candidate will be experienced with Traditional AI including supervised and unsupervised learning, Generative and Agentic AI and containerization. The individual must understand the role AI / ML plays in Healthcare to design and build highly scalable operational and clinical intelligence products.

KEY RESPONSIBILITIES

• Work with business and technical teams to identify functional requirements that drive smart healthcare technology solutions to meet growing organization needs

• Lead the Architecture, design and implementation of Traditional AI, Gen AI and Agentic AI solutions capable of clinical and operational intelligence and decision making, autonomous reasoning and contextual understanding

• Architect and design agentic AI solutions to orchestrate LLM powered multi-agent workflows including RAG enhanced retrieval from multimodal data

• Design and build supervised and unsupervised models, prompt and context engineering solutions and integrate LLMs into modern web and mobile applications which allow feedback and reinforcement learning

• Implement MLOps pipelines for continuous training, monitoring bias/fairness without compromising on quality, performance and uptime.

• Develop and maintain model governance frameworks addressing explainability, bias mitigation and compliance with healthcare data regulations

• Mine and analyze data from internal/external data sets to methodically optimize operations across various departments including intake, clinical, revenue cycle and other operations

• Perform data/error analysis to continuously improve models, clean and validate data for uniformity and accuracy

• Stay ahead of emerging AI trends and research to continuously refine architectural best practices

• Mentor and coach other technical team members on the ethical use of AI, AI architecture design patterns

• Compliance and adherence to all company policies and procedures

• Attends in-office meetings, participates in meetings, and attends educational programs as needed

• Performs other duties as assigned1

QUALIFICATIONS

• At least 10+ years2 of proven experience primarily architecting AI/ML systems in productions environments

• 10+ years3 of experience in both supervised and unsupervised learning, statistics and neural network design

• 7+ years of experience building highly scalable mission critical enterprise grade AI applications at scale

• 5+ years of experience building mission critical health care applications, preferably in home health

• Hands-on experience with LLM’s generative AI frameworks such as Langchain, HuggingFace, OpenAI and Anthropic APIs and Transformer based architectures

• Proven experience with machine learning frameworks such as TensorFlow/Keras, PyTorch and Pandas

• Proven experience with classical data analysis such as Classification, Regression, Clustering and deep learning models such as RNN, CNN, GAN

• Proven experience with various data and AI related services in AWS (Bedrock, Textract, SageMaker, Comprehend)

• Proven experience building scalable solutions leveraging Docker, Kubernetes, AWS ECS

• Expert level knowledge of Python, R

• Proficiency with at-least two scripting languages (e.g. JavaScript, Python, Lua), SQL, No- SQL Databases

• Strong verbal and written communication skills

• Extremely strong analytical and problem-solving abilities

EDUCATION AND CREDENTIALS

• Master’s in Computer Science, Artificial Intelligence, Machine Learning or equivalent experience

We’ll help you put your passion for patient care to work. Apply today!

This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Duties, responsibilities and activities may change or new ones may be assigned at any time with or without notice.

We are an Equal Opportunity Employer.

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 32 points (from 56 before penalties). Reviewed 21 Sep 2026.