Position Overview We are seeking a highly skilled and compliance-minded AI Specialist to design, build, and deploy artificial intelligence and machine learning solutions that drive automation, operational efficiency, and intelligent decision-making across the organization.
This role sits at the intersection of AI engineering, cloud infrastructure, and data security — requiring someone who can build powerful AI systems while operating within strict compliance frameworks including HIPAA and SOC 2.
The ideal candidate is a strong programmer with hands-on AI/ML development experience, deep familiarity with AWS cloud services, and a genuine understanding of what it means to build and deploy AI in regulated, security-sensitive environments.
This is not a theoretical role — you will be building, integrating, and shipping.
Key Responsibilities AI & Machine Learning Development Design, develop, and deploy AI and machine learning models to solve real business problems and automate workflows Build and maintain end-to-end ML pipelines from data ingestion and preprocessing through model training, evaluation, and production deployment Develop natural language processing (NLP), large language model (LLM) integrations, and generative AI solutions as applicable Fine-tune and optimize pre-trained models (including GPT, Claude, or open-source alternatives) for specific use cases Evaluate model performance, monitor for drift, and implement improvements based on real-world feedback Research and apply emerging AI techniques, frameworks, and tools to continuously improve solution quality AI Integration & Automation Integrate AI models and APIs into existing applications, platforms, and workflows Build intelligent automation solutions that reduce manual effort and improve operational throughput Develop AI-powered features including chatbots, recommendation engines, document processing, and predictive analytics Design and implement RAG (Retrieval-Augmented Generation) architectures for knowledge-based AI applications Collaborate with product and operations teams to identify high-value AI use cases and deliver solutions Programming & Software Engineering Write clean, well-documented, production-quality code primarily in Python, with additional languages as needed (JavaScript, SQL, Bash, etc.
) Build APIs, microservices, and data pipelines that support AI workloads at scale Apply software engineering best practices including version control (Git), code review, testing, and CI/CD Maintain and refactor existing codebases for performance, reliability, and maintainability Document technical architectures, implementation decisions, and system behaviors clearly AWS Cloud Infrastructure Architect, deploy, and manage AI and data workloads on AWS cloud infrastructure Utilize AWS services including SageMaker, Lambda, EC2, S3, RDS, Bedrock, Step Functions, and API Gateway Build scalable, cost-efficient cloud architectures that support model training, inference, and data processing Implement infrastructure-as-code using AWS CloudFormation, CDK, or Terraform Monitor cloud resource utilization and optimize for performance and cost Ensure all AWS environments are configured in alignment with security and compliance requirements HIPAA Compliance Design and develop all AI systems and data pipelines in full compliance with HIPAA Privacy and Security Rules Ensure Protected Health Information (PHI) is handled, stored, transmitted, and processed with appropriate safeguards Implement technical controls including encryption at rest and in transit, access controls, and audit logging for all PHI-adjacent systems Participate in HIPAA risk assessments and support remediation of identified vulnerabilities Maintain documentation required for HIPAA compliance including data flow diagrams, system inventories, and access logs Stay current on HIPAA regulatory developments and ensure AI systems remain compliant as regulations evolve SOC 2 Compliance Build and maintain AI systems and cloud infrastructure in accordance with SOC 2 Trust Service Criteria (Security, Availability, Confidentiality, Processing Integrity, and Privacy) Implement and maintain security controls required for SOC 2 Type I and Type II certification Support audit preparation by maintaining evidence, access logs, and system documentation Participate in vulnerability management, penetration testing, and incident response processes Collaborate with security and compliance teams to ensure all AI deployments meet SOC 2 standards Monitor systems continuously for security events and compliance gaps Data Management & Security Design secure data architectures that protect sensitive information throughout the AI pipeline Implement role-based access controls, data masking, and anonymization techniques where appropriate Ensure data governance practices are followed for all datasets used in model training and inference Maintain data lineage documentation and audit trails for compliance and reproducibility Collaboration & Documentation Work closely with engineering, product, operations, and compliance teams to align AI solutions with business needs and regulatory requirements Communicate complex technical concepts clearly to non-technical stakeholders Produce thorough technical documentation for all systems, models, and integrations Mentor junior team members on AI development practices and compliance standards Required Qualifications 3 or more years of hands-on experience in AI, machine learning, or data science engineering roles Strong programming skills in Python — this is the primary development language for this role Demonstrated experience building and deploying ML models or AI-powered applications in production environments Proficiency with AWS cloud services — particularly those relevant to AI/ML workloads (SageMaker, Lambda, S3, EC2, Bedrock, or equivalent) Working knowledge of HIPAA requirements and experience building systems that handle PHI in compliance with applicable regulations Familiarity with SOC 2 compliance frameworks and the technical controls required to support certification Experience with LLMs, NLP, or generative AI frameworks such as LangChain, OpenAI API, Hugging Face, or similar Strong understanding of data security, encryption, access control, and audit logging best practices Excellent written and verbal communication skills, including the ability to document technical work clearly Preferred Qualifications AWS certifications such as AWS Certified Machine Learning Specialty, AWS Solutions Architect, or AWS Security Specialty Experience with MLOps practices and tools including model versioning, monitoring, and automated retraining pipelines Familiarity with vector databases such as Pinecone, Weaviate, or pgvector for RAG implementations Experience in a HIPAA-covered entity or business associate environment Background in healthcare technology, health informatics, or digital health platforms Experience with additional programming languages such as JavaScript, TypeScript, Go, or Java Familiarity with containerization and orchestration tools including Docker and Kubernetes Technical Stack Core Python — primary language AWS — SageMaker, Lambda, S3, EC2, Bedrock, Step Functions, API Gateway, CloudFormation / CDK LLM frameworks — LangChain, OpenAI API, Anthropic API, Hugging Face Data & Infrastructure SQL and NoSQL databases Vector databases for semantic search and RAG Git / GitHub — version control and CI/CD Docker / Kubernetes — containerization and orchestration Compliance & Security HIPAA Privacy and Security Rule compliance SOC 2 Trust Service Criteria AWS security services — IAM, KMS, CloudTrail, GuardDuty, Security Hub This is a 100% Remote Job Full time Rate is $10/hr
