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Sr AI/ML Full Stack Engineer
Job in
Rochester, Olmsted County, Minnesota, 55905, USA
Listed on 2026-09-04
Listing for:
Horizontal Talent
Full Time
position Listed on 2026-09-04
Job specializations:
-
Software Development
AI Engineer (Applied/Software), DevOps, Machine Learning/ ML Engineer, Cloud Engineer - Software
Job Description & How to Apply Below
Position Overview
We are seeking a Senior AI/ML Full Stack Engineer to design, build, evaluate, and deploy production-grade AI/ML and Generative AI solutions. This role combines hands-on AI/ML engineering with full-stack application development, cloud-native deployment, and MLOps/Dev Ops practices.
The engineer will develop end-to-end AI-enabled applications incorporating large language models (LLMs), machine learning, document intelligence, semantic search, APIs, structured and unstructured data, and modern user interfaces.
Key Responsibilities- Design, develop, evaluate, and deploy production-grade Generative AI, LLM, and machine learning applications.
- Build LLM-powered assistants, document intelligence solutions, semantic search capabilities, embedding pipelines, and AI-enabled enterprise applications.
- Develop document ingestion, processing, chunking, retrieval, and data integration workflows.
- Implement prompt engineering, query expansion, citation generation, and retrieval-augmented AI capabilities.
- Develop evaluation frameworks measuring answer relevance, context relevance, faithfulness, hallucination reduction, and citation accuracy.
- Implement AI safety and Responsible AI controls, including guardrails, content moderation, blocked topics, and escalation logic.
- Build responsive front-end applications, backend services, RESTful APIs, authentication/authorization, and integrations with AI/ML services.
- Design and maintain CI/CD pipelines using Azure Dev Ops for automated builds, testing, security validation, and deployment.
- Implement automated unit and integration testing, environment configuration, branching strategies, release management, and deployment automation.
- Containerize and deploy applications using Docker and cloud-native technologies.
- Establish production monitoring, logging, observability, performance tracking, and troubleshooting for AI models and applications.
- Apply strong software engineering and MLOps practices including modular architecture, reusable components, version control, code reviews, testing, security, and performance optimization.
- Collaborate with product owners, business stakeholders, architects, Dev Ops engineers, security teams, and other technical teams throughout the development lifecycle.
- Translate business requirements into secure, scalable, measurable, and maintainable technical solutions.
- Strong hands-on development experience with Python and SQL.
- Proven experience building and deploying production-grade Generative AI and LLM applications.
- Experience with LLMs, prompt engineering, embeddings, semantic search, query expansion, and citation generation.
- Experience developing, evaluating, deploying, and monitoring ML/NLP models.
- Understanding of LLM evaluation techniques including relevance, faithfulness, hallucination reduction, and citation accuracy.
- Experience implementing AI safety guardrails and Responsible AI controls.
- Strong full-stack development experience, including modern front-end frameworks, backend development, REST APIs, authentication, and application integrations.
- Experience building CI/CD pipelines with Azure Dev Ops.
- Strong knowledge of Git, automated testing, build/deployment pipelines, release management, and environment configuration.
- Experience with at least one major cloud platform:
Azure, GCP, AWS, or OCI. - Experience with containerized application development and deployment using Docker.
- Experience designing and integrating APIs and AI/ML services into enterprise applications.
- Experience with production monitoring, logging, observability, troubleshooting, and application/model performance tracking.
- Strong understanding of secure software development, data privacy, and enterprise application development practices.
- Strong communication and cross-functional collaboration skills.
- Azure Dev Ops
- Vertex AI
- AWS Bedrock
- Amazon Sage Maker
- Big Query
- Snowflake
- Open Search
- Cloud Run
- Docker
- Airflow
- Terraform
- Comparable cloud, AI/ML, MLOps, and Dev Ops technologies
- Experience developing AI solutions using healthcare, clinical, claims, life sciences, regulatory, or other complex…
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