AI & Cloud Engineering

<h3>Position Overview </h3><p>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. </p><p>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. </p><h3>Key Responsibilities </h3><h3>AI &amp; Machine Learning Development </h3><ul><li>Design, develop, and deploy AI and machine learning models to solve real business problems and automate workflows </li></ul><ul><li>Build and maintain end-to-end ML pipelines from data ingestion and preprocessing through model training, evaluation, and production deployment </li></ul><ul><li>Develop natural language processing (NLP), large language model (LLM) integrations, and generative AI solutions as applicable </li></ul><ul><li>Fine-tune and optimize pre-trained models (including GPT, Claude, or open-source alternatives) for specific use cases </li></ul><ul><li>Evaluate model performance, monitor for drift, and implement improvements based on real-world feedback </li></ul><ul><li>Research and apply emerging AI techniques, frameworks, and tools to continuously improve solution quality </li></ul><h3>AI Integration &amp; Automation </h3><ul><li>Integrate AI models and APIs into existing applications, platforms, and workflows </li></ul><ul><li>Build intelligent automation solutions that reduce manual effort and improve operational throughput </li></ul><ul><li>Develop AI-powered features including chatbots, recommendation engines, document processing, and predictive analytics </li></ul><ul><li>Design and implement RAG (Retrieval-Augmented Generation) architectures for knowledge-based AI applications </li></ul><ul><li>Collaborate with product and operations teams to identify high-value AI use cases and deliver solutions </li></ul><h3>Programming &amp; Software Engineering </h3><ul><li>Write clean, well-documented, production-quality code primarily in Python, with additional languages as needed (JavaScript, SQL, Bash, etc.) </li></ul><ul><li>Build APIs, microservices, and data pipelines that support AI workloads at scale </li></ul><ul><li>Apply software engineering best practices including version control (Git), code review, testing, and CI/CD </li></ul><ul><li>Maintain and refactor existing codebases for performance, reliability, and maintainability </li></ul><ul><li>Document technical architectures, implementation decisions, and system behaviors clearly </li></ul><h3>AWS Cloud Infrastructure </h3><ul><li>Architect, deploy, and manage AI and data workloads on AWS cloud infrastructure </li></ul><ul><li>Utilize AWS services including SageMaker, Lambda, EC2, S3, RDS, Bedrock, Step Functions, and API Gateway </li></ul><ul><li>Build scalable, cost-efficient cloud architectures that support model training, inference, and data processing </li></ul><ul><li>Implement infrastructure-as-code using AWS CloudFormation, CDK, or Terraform </li></ul><ul><li>Monitor cloud resource utilization and optimize for performance and cost </li></ul><ul><li>Ensure all AWS environments are configured in alignment with security and compliance requirements </li></ul><h3>HIPAA Compliance </h3><ul><li>Design and develop all AI systems and data pipelines in full compliance with HIPAA Privacy and Security Rules </li></ul><ul><li>Ensure Protected Health Information (PHI) is handled, stored, transmitted, and processed with appropriate safeguards </li></ul><ul><li>Implement technical controls including encryption at rest and in transit, access controls, and audit logging for all PHI-adjacent systems </li></ul><ul><li>Participate in HIPAA risk assessments and support remediation of identified vulnerabilities </li></ul><ul><li>Maintain documentation required for HIPAA compliance including data flow diagrams, system inventories, and access logs </li></ul><ul><li>Stay current on HIPAA regulatory developments and ensure AI systems remain compliant as regulations evolve </li></ul><h3>SOC 2 Compliance </h3><ul><li>Build and maintain AI systems and cloud infrastructure in accordance with SOC 2 Trust Service Criteria (Security, Availability, Confidentiality, Processing Integrity, and Privacy) </li></ul><ul><li>Implement and maintain security controls required for SOC 2 Type I and Type II certification </li></ul><ul><li>Support audit preparation by maintaining evidence, access logs, and system documentation </li></ul><ul><li>Participate in vulnerability management, penetration testing, and incident response processes </li></ul><ul><li>Collaborate with security and compliance teams to ensure all AI deployments meet SOC 2 standards </li></ul><ul><li>Monitor systems continuously for security events and compliance gaps </li></ul><h3>Data Management &amp; Security </h3><ul><li>Design secure data architectures that protect sensitive information throughout the AI pipeline </li></ul><ul><li>Implement role-based access controls, data masking, and anonymization techniques where appropriate </li></ul><ul><li>Ensure data governance practices are followed for all datasets used in model training and inference </li></ul><ul><li>Maintain data lineage documentation and audit trails for compliance and reproducibility </li></ul><h3>Collaboration &amp; Documentation </h3><ul><li>Work closely with engineering, product, operations, and compliance teams to align AI solutions with business needs and regulatory requirements </li></ul><ul><li>Communicate complex technical concepts clearly to non-technical stakeholders </li></ul><ul><li>Produce thorough technical documentation for all systems, models, and integrations </li></ul><ul><li>Mentor junior team members on AI development practices and compliance standards </li></ul><h3>Required Qualifications </h3><ul><li>3 or more years of hands-on experience in AI, machine learning, or data science engineering roles </li></ul><ul><li>Strong programming skills in Python — this is the primary development language for this role </li></ul><ul><li>Demonstrated experience building and deploying ML models or AI-powered applications in production environments </li></ul><ul><li>Proficiency with AWS cloud services — particularly those relevant to AI/ML workloads (SageMaker, Lambda, S3, EC2, Bedrock, or equivalent) </li></ul><ul><li>Working knowledge of HIPAA requirements and experience building systems that handle PHI in compliance with applicable regulations </li></ul><ul><li>Familiarity with SOC 2 compliance frameworks and the technical controls required to support certification </li></ul><ul><li>Experience with LLMs, NLP, or generative AI frameworks such as LangChain, OpenAI API, Hugging Face, or similar </li></ul><ul><li>Strong understanding of data security, encryption, access control, and audit logging best practices </li></ul><ul><li>Excellent written and verbal communication skills, including the ability to document technical work clearly </li></ul><h3>Preferred Qualifications </h3><ul><li>AWS certifications such as AWS Certified Machine Learning Specialty, AWS Solutions Architect, or AWS Security Specialty </li></ul><ul><li>Experience with MLOps practices and tools including model versioning, monitoring, and automated retraining pipelines </li></ul><ul><li>Familiarity with vector databases such as Pinecone, Weaviate, or pgvector for RAG implementations </li></ul><ul><li>Experience in a HIPAA-covered entity or business associate environment </li></ul><ul><li>Background in healthcare technology, health informatics, or digital health platforms </li></ul><ul><li>Experience with additional programming languages such as JavaScript, TypeScript, Go, or Java </li></ul><ul><li>Familiarity with containerization and orchestration tools including Docker and Kubernetes </li></ul><h3>Technical Stack </h3><h3>Core </h3><ul><li>Python — primary language </li></ul><ul><li>AWS — SageMaker, Lambda, S3, EC2, Bedrock, Step Functions, API Gateway, CloudFormation / CDK </li></ul><ul><li>LLM frameworks — LangChain, OpenAI API, Anthropic API, Hugging Face </li></ul><h3>Data &amp; Infrastructure </h3><ul><li>SQL and NoSQL databases </li></ul><ul><li>Vector databases for semantic search and RAG </li></ul><ul><li>Git / GitHub — version control and CI/CD </li></ul><ul><li>Docker / Kubernetes — containerization and orchestration </li></ul><h3>Compliance &amp; Security </h3><ul><li>HIPAA Privacy and Security Rule compliance </li></ul><ul><li>SOC 2 Trust Service Criteria </li></ul><ul><li>AWS security services — IAM, KMS, CloudTrail, GuardDuty, Security Hub </li></ul><h3>Requirements</h3><h3>This is a 100% Remote Job</h3><h3>Full time</h3><h3>Rate is $10/hr</h3><p>Originally posted on <a href="https://himalayas.app">Himalayas</a></p>