AI/ML Engineer

AI/ML Engineer
Contract End Date: 3/31/27
Remote

Position Overview:
We are seeking a Senior AI/ML Engineer with strong hands-on experience designing, building, evaluating, and deploying production-grade AI/ML and Generative AI solutions. This role will focus on healthcare and enterprise AI applications, including LLM-powered assistants, document intelligence, machine learning pipelines, full-stack application development, and cloud-native deployment.
Top Skills:

• Generative AI / LLM Application Development Hands-on experience building production-grade LLM applications, including prompt engineering, embeddings, semantic search, query expansion, citation generation, and RAG-style architectures.
• Python & SQL Strong Python programming for AI/ML and backend development, combined with SQL for querying, transforming, and analyzing enterprise data.
• AI/ML Engineering & MLOps Experience developing, evaluating, deploying, and monitoring ML/LLM solutions, including LLM evaluation metrics, hallucination reduction, safety guardrails, CI/CD, cloud platforms, Docker, observability, and production troubleshooting.

Job Description:

• The candidate will be responsible for designing and developing scalable AI solutions that combine large language models, structured and unstructured data, cloud services, machine learning components, APIs, and user-facing applications. Responsibilities include developing document ingestion and processing workflows, semantic search, embeddings, prompt engineering, evaluation frameworks, AI safety guardrails, APIs, production monitoring, and end-to-end AI-enabled applications.
• The candidate will also be responsible for full-stack development, including building responsive user interfaces, backend services, RESTful APIs, data integrations, authentication and authorization, and integrations with AI/ML models and cloud-based services.
  The role will include designing, building, and maintaining CI/CD pipelines using
• Azure DevOps to automate application build, testing, validation, security checks, and deployment across development, testing, staging, and production environments. Responsibilities may include Azure DevOps Pipelines, Git-based source control, branching strategies, automated unit and integration testing, environment configuration, release management, deployment automation, and troubleshooting deployment issues.
• The candidate will be expected to follow strong software engineering and MLOps practices across the development lifecycle, including modular architecture, reusable components, version control, automated testing, code reviews, logging, observability, error handling, performance optimization, security, maintainability, and production support.
• The role will also require close collaboration with product owners, clinical or business stakeholders, architects, DevOps engineers, security teams, and other technical teams to gather and translate requirements, communicate technical decisions and tradeoffs, and deliver reliable, secure, measurable, and maintainable AI solutions.

Required Skills:

• Strong Python programming and SQL experience
• Hands-on experience building production-grade Generative AI and LLM-powered applications
• Experience with LLMs, prompt engineering, embeddings, semantic search, query expansion, and citation generation
• Experience with ML/NLP model development, evaluation, deployment, and performance monitoring
• Familiarity with LLM evaluation metrics such as answer relevance, context relevance, faithfulness, hallucination reduction, and citation accuracy
• Experience implementing AI safety guardrails, content moderation, blocked topics, escalation logic, and responsible AI controls
• Experience with full-stack application development, including modern front-end frameworks, backend services, REST APIs, authentication, and application integration
• Experience designing and developing CI/CD pipelines using Azure DevOps
• Experience with Git-based source control, automated testing, build pipelines, deployment pipelines, release management, and environment configuration
• Experience with cloud platforms such as Azure, Google Cloud Platform, AWS, or OCI
• Experience with tools and technologies such as Azure DevOps, Vertex AI, AWS Bedrock, SageMaker, BigQuery, Snowflake, OpenSearch, Cloud Run, Docker, Airflow, Terraform, or comparable cloud and MLOps technologies
• Experience with containerized application development and deployment using Docker
• Experience designing and consuming APIs and integrating AI/ML services into enterprise applications
• Experience with production monitoring, logging, observability, model/application performance tracking, and troubleshooting
• Experience working with healthcare, claims, clinical, regulatory, life sciences, or enterprise data preferred
• Strong understanding of secure software development, data privacy, and enterprise application development practices
• Strong communication skills and ability to collaborate effectively with both technical and non-technical stakeholders

• Bachelor s degree required in Computer Science, Data Science, Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related technical field.
• Master s degree or higher preferred in Data Science, Computer Science, Biomedical Engineering, Artificial Intelligence, Machine Learning, Engineering, or a related field.