Job at a glance
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 Enable