AI Architect

$100K - $110K Sunrise, FL, US Mid Level AI Architect

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Skills & Technologies

AwsAzureOpenaiPrompt EngineeringPythonPytorchRagSagemakerTensorflow

About This Role

AI job market dashboard showing open roles by category

Position Summary: The AI Architect will be responsible for designing, implementing, and managing AI systems crucial to the organization’s operations. This role includes ensuring the performance, availability, and security of these systems. The AI Architect will work closely with the development team and other business units to align AI solutions with organizational needs and regulatory standards, particularly within the health plan sector.

Essential Duties and Responsibilities:

  • Design, implement, and manage AI systems that meet both performance and security standards.
  • Analyze organizational needs and maintain AI solutions to support these requirements.
  • Ensure AI system performance, availability, and security are maintained at all times.
  • Develop and maintain AI architectures and data structures that align with business needs.
  • Implement backup and recovery plans to ensure data integrity and availability.
  • Work closely with the development team to optimize AI model usage and improve performance.
  • Provide technical support and guidance to resolve AI system issues and malfunctions.
  • Collaborate with other business units to understand future needs and adapt AI strategies accordingly.
  • Conduct regular security audits and compliance checks, particularly focusing on health plan data protection regulations such as HIPAA.
  • Prepare and present reports on AI status, performance, and strategic development to senior management.
  • Evaluate and recommend emerging AI technologies, frameworks, and tools for organizational adoption.
  • Develop AI governance policies, standards, and best practices to ensure responsible AI usage across the organization.
  • Mentor and guide development team members on AI/ML concepts, tools, and implementation patterns.
  • Design and oversee data pipelines and ETL processes to support AI/ML model training and deployment.
  • Performs other related duties as assigned.

This job description in no way states or implies that these are the only duties performed by the employee occupying this position. Employees will be required to perform any other job\-related duties assigned by their supervisor or management.

Qualifications:

REQUIRED

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field required.
  • At least 5 years of experience in AI/ML system development and management.
  • Minimum 3 years of experience with AI architecture design, model deployment, and data engineering.
  • Expertise in AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit\-learn, Azure AI Services).
  • Strong familiarity with cloud services such as Microsoft Azure or Amazon Web Services (AWS).
  • Proficiency in machine learning algorithms, data integration, and model lifecycle management.
  • Experience with ETL processes and data pipelines.
  • Strong problem\-solving and communication skills.
  • Ability to work both independently and as part of a team.

PREFERRED

  • Master’s degree in Artificial Intelligence, Machine Learning, Data Science, or related field.
  • Relevant professional certifications (e.g., Microsoft Azure AI Engineer, AWS Machine Learning Engineer, Google Professional ML Engineer).
  • Experience with large language models (LLMs), generative AI, and prompt engineering.
  • Experience with cloud\-native AI/ML services (Azure OpenAI, Azure Machine Learning, AWS SageMaker).
  • Experience in a healthcare or health plan environment with understanding of HIPAA compliance requirements.
  • Understanding of ASC X12 standards for healthcare electronic data interchange such as:

+ - Medical Claims Interface – 837

  • Benefit Enrollment – 834
  • Claim File – 999
  • Claim Status – 276/277
  • Experience with CI/CD pipelines and DevOps practices for AI/ML model deployment (MLOps).
  • Familiarity with responsible AI principles, bias detection, and model explainability techniques.
  • Experience with vector databases, RAG (Retrieval\-Augmented Generation) architecture, and semantic search.
  • Knowledge of Natural Language Processing (NLP) and computer vision applications.

Skills and Abilities:

  • Deep technical expertise in AI principles, machine learning, deep learning, and data modeling methodologies.
  • Excellent verbal and written communication skills.
  • Strong analytical and problem\-solving skills, with the ability to manage multiple tasks efficiently.
  • Excellent organizational skills and attention to detail.
  • + Excellent communication and interpersonal skills, capable of explaining complex AI concepts to non\-technical stakeholders.
  • Experience working in a team environment.
  • Excellent time management skills with the proven ability to meet deadlines.
  • Extensive knowledge of the following:

+ - Python, R, or similar ML/AI programming languages

  • SQL and database management systems
  • Cloud AI/ML platforms (Azure AI, AWS SageMaker)
  • API development and integration (REST, GraphQL)
  • Data visualization and reporting tools
  • Commitment to continuous learning and adapting to new technologies and industry trends.
  • Proficient with Microsoft Office Suite or related software.

Work Schedule:

Community Care Plan is currently following a hybrid work schedule. The company reserves the right to change the work schedules based on the company needs.

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. A reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to sit, use hands, reach with hands and arms, and talk or hear. The employee is frequently required to stand, walk, and sit. The employee may occasionally be required to stoop, kneel, crouch or crawl. The employee may occasionally lift and/or move up to 15 pounds.

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of the job. The environment includes work inside/outside the office, travel to other offices, as well as domestic travel. A reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The noise level in the work environment is usually moderate.

We are an equal opportunity employer who recruits, employs, trains, compensates and promotes regardless of age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio\-economic status, veteran status, and other characteristics that make our employees unique. We are committed to fostering, cultivating, and preserving a culture of diversity, equity, and inclusion.

Background Screening Notice:

In compliance with Florida law, candidates selected for this position must complete a Level 2 background screening through the Florida Care Provider Background Screening Clearinghouse.

The Clearinghouse is a statewide system managed by the Agency for Health Care Administration (AHCA) and is designed to help protect children, seniors, and other vulnerable populations while streamlining the screening process for employers and applicants.

Additional information is available at: https://info.flclearinghouse.com

Salary Context

This $100K-$110K range is in the lower quartile for AI Architect roles in our dataset (median: $180K across 25 roles with salary data).

Role Details

Title AI Architect
Location Sunrise, FL, US
Category AI Architect
Experience Mid Level
Salary $100K - $110K
Remote No

About This Role

This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.

The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.

Across the 3,824 AI roles we're tracking, AI Architect positions make up 1% of the market. At South Florida Community Care Network, this role fits into their broader AI and engineering organization.

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

What the Work Looks Like

Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

Skills Required

Aws (31% of roles) Azure (23% of roles) Openai (12% of roles) Prompt Engineering (15% of roles) Python (51% of roles) Pytorch (15% of roles) Rag (23% of roles) Sagemaker (5% of roles) Tensorflow (13% of roles)

Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.

Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.

Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.

Compensation Benchmarks

AI Architect roles pay a median of $220,000 based on 92 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($105K) sits 52% below the category median. Disclosed range: $100K to $110K.

Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.

South Florida Community Care Network AI Hiring

South Florida Community Care Network has 1 open AI role right now. They're hiring across AI Architect. Based in Sunrise, FL, US. Compensation range: $110K - $110K.

Location Context

Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).

Career Path

Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.

From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.

Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.

What to Expect in Interviews

AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.

When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.

AI Hiring Overview

The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.

The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

The AI Job Market Today

The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 92 roles with disclosed compensation, the median salary for AI Architect positions is $220,000. Actual compensation varies by seniority, location, and company stage.
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
About 16% of the 3,824 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
South Florida Community Care Network is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Architect positions include Senior Engineer, AI Architect, Engineering Manager, Principal Engineer. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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