W2 - (2) - AI/ML Engineer (LLM, AI, RAG, Python, SQL, Cloud, HIPAA, MCP, LangChain) - Remote

Description Description: Duties:Job Summary:Al/ML Engineers at client Clinic play a pivotal role in the union of data, systems, and computer sciences. They work closely with a multidisciplinary team, including clinicians, user experience designers, product managers, IT professionals, and external partners, to develop and deploy effective, efficient, and ethical Al/ML solutions into clinical practice to enhance patient care and operational efficiency. As an Al/ML Engineer, you may work on the full spectrum of the Al life cycle from ideation to production. You understand the clinical environment well, including workflows, challenges, and requirements of healthcare providers and patients. You will leverage advanced techniques in Al/ML to analyze vast amounts of healthcare data, including patient records, medical imaging, and genomic information, to develop Al solutions that meet clinical needs and are integrated smoothly into clinical processes. You will develop, integrate, and standardize software components and create, maintain, and follow quality system procedures. You will work on the engineering of systems that are pivotal to developing and deploying these solutions, which encompass everything from design requirements, development, component creation, verification, non-clinical validation, and risk mitigation to ensure our digital health technology products meet and exceed regulatory requirements and setting new benchmarks for safety and effectiveness in clinical settings. Your expertise will also extend to facilitating consistent and automated Al software solution development and releases through the design, testing, and maintenance of tools and associated Cl/CD pipelines. JobResponsibilitiesWorking on component design, development, integration, and standardization to create Al-driven solutions that seamlessly integrate into clinical practice to enhance patient care and clinic operations.Collaborating with a multidisciplinary team, including clinicians, user experience designers, product managers, and IT professionals, to understand user needs, workflows, and clinical requirements and assess feasibility. Translating user feedback and requirements into design concepts and usability specifications for Al solutions.Interpreting/ analyzing data to inform strategic decisions and communicate complex findings in easily understandable terms to bridge the gap between Al technologies and clinical applications.Leveraging machine learning techniques such as deep learning, natural language processing, computer vision, large language models, etc., to design, develop and deploy end-to-end Al solutions for healthcare applications.Participating in the engineering of systems crucial for developing and deploying Al solutions.Facilitating consistent and automated Al software solution development and releases through the design, testing, and maintenance of tools and associated Cl/CD pipelines.Contributing to implementing the best practices and standards for Al development and deployment methodologies, tools, and platforms.Providing training and education to healthcare staff on the use of Al tools and technologies.SkillsLLMAIRequired Skills & ExperienceExperience applying Al and machine learning in production environments, showcasing an understanding of healthcare technology.Skill in cloud infrastructure environment and software development tools.Experience working with large, complex, and heterogeneous data sets, preferably in healthcare.Skill in Al/ML techniques and frameworks.-History of collaborating across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.Familiarity with best practices in data engineering, data science, Al Engineering, and the MLOps communities.Strong interpersonal, communication, and time management skills.Preferred Skills & ExperienceA Ph.D. in engineering, computer science, health science, or a related analytical/quantitative field is preferred.Expertise in Al/ML techniques and frameworks, such as deep learning, natural language processing, and Generative Al, with proficiency in tools like Python, TensorFlow, PyTorch, sci-kit-learn, Keras, etc.Knowledge of the healthcare domain, including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards.Familiarity with systems or quality engineering best practices, regulatory standards, and compliance frameworks, with the ability to adapt these effectively to different project scenarios.Expertise in user-centered design, human factors engineering, usability testing methodologies, and evaluation across Al product development. Ability to conduct expert reviews using established usability practices and methods. Presents findings in easy-to-understand terms for the business or clinical practice.Ability to articulate complex technical concepts to diverse audiences, facilitating clear understanding and engagement from technical and non-technical stakeholders.Ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends.Experience with healthcare industry informatics standards, best practices, and common data models.Education Required Education:-Master's degree in Engineering, Computer Science, mathematics, health science, or a related field AND one (1) year experience. (Escalate for approval if Master's degree is not in any of the specified fields of study).OR-Bachelor's degree with three (3) years of experience.OR-HS Diploma/GED with Seven (7) years of experience may be considered.Schedule Notes Role Summary:AI/ML software engineers to design and build production AI systems for healthcare. The role spans AI system design (agent architectures, evaluation, guardrails) and production software engineering (Python services, data pipelines, cloud deployment). We are hiring multiple contractors; specific strengths can differ across candidates.Core ResponsibilitiesDesign and implement Agentic AI systems - LLM integrations, prompt engineering, MCP servers, agent architectures.Build and maintain Python services, automation workflows, and data pipelines (including RAG with embeddings and vector databases).Implement evaluation frameworks and guardrails for LLM/agent systems before production.Deploy, monitor, and optimize ML/AI solutions in the cloud.Collaborate with product, data, and engineering teams; uphold code quality, performance, security, and maintainability.Technical RequirementsExperience : 7+ years of software/ML engineering, with recent hands-on AI/LLM work.Python : Advanced; production experience with APIs, async, and testing.AI / LLM agents : Designing and implementing autonomous or semi-autonomous agents (tool- using, planners, orchestrators).Agent frameworks : Hands-on with at least one (LangChain, LangGraph, LlamaIndex, Semantic Kernel, Google ADK).MCP : Agent communication, coordination, or protocol-driven AI architectures.Evaluation & guardrails : Prompt regression tests, hallucination and quality metrics, and guardrails for PII, jailbreaks, and unsafe outputs.ML lifecycle : ML pipelines, deployment, evaluation, monitoring; embedding models, vector DBs, and RAG.Data management : Modeling, pipelines, SQL/NoSQL, data quality and governance at scale.Cloud : Hands-on in Azure, AWS, or GCP; cloud-native deployment patterns and CI/CD.HIPAA / PHI : Working knowledge of PHI handling in AI - BAA-covered model endpoints, no PHI in training data or logs, de-identification before prompt context.Preferred Technical SkillsAI/LLM Agent and MCP tooling Google ADK, Copilot Studio.Cloud Experience Google Cloud or Azure preferred.Database Knowledge BigQuery, Firestore, Cloud SQL, etc.Data pipeline Dataflow.Power Automate.Automation Tooling UiPath, etc.CI/CD Pipeline Azure DevOps Pipeline.Infrastructure as Code (IaC) Terraform.Other Requirements Rapid experimentation: AI moves fast; continuously evaluates new models, capabilities, and emerging patterns (MCP, A2A, agent frameworks).Healthcare context: AI/ML in this environment requires healthcare grounding, not generic model building.Proactive: Proposes AI-assisted solutions; tests what is possible and shares findings.Independent operator: Works with minimal supervision in fast-moving environments; strong documentation and cross-functional collaboration.MLOps or LLMOps experience.Streaming or event-driven architectures.Prior enterprise or large-scale data management.Hours Per Day 8.00Hours Per Week 40.00Pay rate $80/hr on W2.#J-18808-Ljbffr