Company Overview

At Enlyte, we combine innovative technology, clinical expertise, and human compassion to help people recover after workplace injuries or auto accidents. We support their journey back to health and wellness through our industry-leading solutions and services. Whether you're supporting a Fortune 500 client or a local business, developing cutting-edge technology, or providing clinical services you'll work alongside dedicated professionals who share your commitment to excellence and make a meaningful impact. Join us in fueling our mission to protect dreams and restore lives, while building your career in an environment that values collaboration, innovation, and personal growth.

 

Be part of a team that makes a real difference.

Job Description

This is a full-time remote position that can be located anywhere in the U.S

We are seeking an experienced AI Architect to lead the design, development, and governance of enterprise-grade AI and Agentic AI solutions and standards across the organization. This role sits at the intersection of cloud-native AI engineering, data architecture, and AI governance — shaping how the company builds, deploys, and scales intelligent systems.

The ideal candidate brings deep hands-on expertise with the AWS AI/ML stack, a strong foundation in data governance and data architecture, and a forward-looking vision for agentic AI enablement. You will be a strategic technical leader who can translate business objectives into scalable AI architectures while ensuring responsible, governed, and secure AI practices.

 

Key Responsibilities:

AI Architecture & Strategy

• Define and own the enterprise AI reference architecture, including patterns for model training, inference, orchestration, and agentic workflows.
• Evaluate, select, and integrate AWS AI/ML services into a cohesive, scalable platform strategy.
• Architect end-to-end AI solutions — from data ingestion and feature engineering through model deployment, monitoring, and feedback loops.
• Lead the technical design of Agentic AI systems, including multi-agent orchestration, tool-use patterns, retrieval-augmented generation (RAG), and autonomous decision-making workflows.

AWS AI Stack Expertise

• Serve as the subject matter expert on the AWS AI ecosystem, including but not limited to:
• Amazon SageMaker — model training, fine-tuning, hosting, endpoints, Pipelines, Feature Store, Model Registry, and Ground Truth.
• Amazon Bedrock — foundation model access, custom model import, Guardrails, Knowledge Bases, and Agents.
• AWS Agent Core — agentic runtime orchestration, tool integration, and session management.
• Amazon Q — enterprise AI assistant capabilities, customization, and integration.
• Amazon Kendra / OpenSearch — enterprise search, semantic retrieval, and RAG pipelines.
• AWS Step Functions & EventBridge — workflow orchestration for AI pipelines and event-driven architectures.
• Amazon Comprehend, Textract, Rekognition, Transcribe, Polly — applied AI services for NLP, document processing, vision, and speech.
• AWS Lambda, ECS/EKS, App Runner — serverless and containerized inference hosting.
• Amazon CloudWatch, SageMaker Model Monitor — observability, drift detection, and model performance tracking.

Data Governance & Data Architecture for AI

• Design and enforce data governance frameworks that ensure data quality, lineage, cataloging, and compliance across AI workloads.
• Architect data pipelines and storage strategies optimized for AI/ML development (feature stores, data lakes, lakehouses).
• Collaborate with data engineering teams to establish robust data contracts, schemas, and metadata standards.
• Ensure AI training data and inference data meet regulatory, ethical, and privacy requirements (e.g., PII handling, bias detection, GDPR/CCPA alignment).
• Leverage AWS data governance tools including AWS Glue Data Catalog, AWS Lake Formation, Amazon DataZone, and AWS CloudTrail for audit and lineage.

Agentic AI Enablement

• Design frameworks and patterns for building, deploying, and managing autonomous AI agents at enterprise scale.
• Define standards for agent tool-use, memory management, guardrails, human-in-the-loop escalation, and multi-agent collaboration.
• Establish evaluation and testing frameworks for agentic systems (accuracy, safety, latency, cost).
• Partner with product and engineering teams to identify and prioritize agentic AI use cases.

Leadership & Collaboration

• Mentor engineers and data scientists on AI architecture best practices and AWS tooling.
• Collaborate with security, compliance, and legal teams to embed responsible AI principles into the development lifecycle.
• Present architectural recommendations and roadmaps to senior leadership and stakeholders.
• Stay current on emerging AI technologies, foundation models, and AWS service launches; evaluate their applicability to enterprise needs.

Qualifications

• Bachelor’s Degree in Computer Science, Software Engineering, or related field
• 8+ years of experience in software architecture, data architecture, or AI/ML engineering, with at least 3 years in a senior or lead architect role.
• Deep, hands-on expertise with the AWS AI/ML stack (SageMaker, Bedrock, Agent Core, Kendra, Comprehend, etc.).
• Strong foundation in data architecture — data modeling, ETL/ELT pipelines, data lakes, lakehouses, and cloud-native data platforms.
• Proven experience in data governance — data quality frameworks, metadata management, data cataloging, lineage tracking, and compliance.
• Experience designing and deploying large language model (LLM) solutions, including prompt engineering, fine-tuning, RAG, and embedding strategies.
• Demonstrated experience with agentic AI patterns — multi-agent systems, tool orchestration, autonomous workflows, and guardrail design.
• Strong understanding of MLOps practices — CI/CD for ML, model versioning, A/B testing, monitoring, and retraining pipelines.
• Proficiency in Python and familiarity with ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar).
• Experience with infrastructure-as-code (CloudFormation, CDK, Terraform) for AI/ML resource provisioning.
• Excellent communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders.

 

Preferred Qualifications

• AWS certifications — Solutions Architect Professional, Machine Learning Specialty, or Data Analytics Specialty.
• Experience with Amazon DataZone, AWS Lake Formation, and AWS Glue for governed data sharing and cataloging.
• Familiarity with graph databases (Neptune, Neo4j) for knowledge graph–driven AI applications.
• Experience building multi-modal AI solutions (text, image, video, audio).
• Background in insurance, healthcare, or regulated industries where data governance and compliance are paramount.
• Experience with cost optimization strategies for AI workloads at scale.

Benefits

We’re committed to supporting your ultimate well-being through our total compensation package offerings that support your health, wealth and self. These offerings include Medical, Dental, Vision, Health Savings Accounts / Flexible Spending Accounts, Life and AD&D Insurance, 401(k), Tuition Reimbursement, and an array of resources that encourage a lifetime of healthier living. Benefits eligibility may differ depending on full-time or part-time status. Compensation depends on the applicable US geographic market. The expected base pay for this position ranges from $133,000 - $180,000 annually, and will be based on a number of additional factors including skills, experience, and education.  

 

The Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.  

 

Don’t meet every single requirement? Studies have shown that women and underrepresented minorities are less likely to apply to jobs unless they meet every single qualification. We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

#LI-Remote

#LI-FP1

 

 

Bachelor's degree in computer science, software engineering, or related field; 8+ years in software, data, or AI/ML architecture; 3+ years in senior or lead architect roles; AWS AI/ML, data governance, LLM, MLOps, and Python expertise.

Key Responsibilities

• architecting solutions
• defining standards
• mentoring engineers

Skills & Tools

AWS, Amazon SageMaker, Amazon Bedrock, AWS Agent Core, Amazon Kendra, Amazon Comprehend, Python, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, CloudFormation, CDK, Terraform, Amazon DataZone, AWS Lake Formation, AWS Glue, Neptune, Neo4j, OpenSearch, Amazon Q, AWS Step Functions, EventBridge, Amazon Textract, Amazon Rekognition, Amazon Transcribe, Amazon Polly, AWS Lambda, ECS, EKS, App Runner, Amazon CloudWatch, SageMaker Model Monitor, AWS CloudTrail

Job Details

• Category: Software Development
• Seniority: Senior Level
• Commitment: Full Time
• Workplace: Remote — United States
• Salary: USD 133,000 – 180,000 / year
• Languages: English

Benefits

• 401k matching
• Tuition reimbursement
• Retirement plan

About Enlyte

A technology and clinical services company helping people recover from workplace injuries and auto accidents. — Industry: Information Technology