Sr AI/ML Full Stack Engineer

Horizontal Talent; Rochester (MN); On-site; USD 70,000 - 123,000; Full time

Job summary

Horizontal Talent is seeking a Senior AI/ML Full Stack Engineer to design, build, and deploy production-grade AI/ML and Generative AI solutions. This role blends hands-on AI/ML engineering with full-stack app development, cloud-native deployment, and MLOps practices.

You will work on end-to-end AI-enabled applications using LLMs, semantic search, document intelligence, and modern user interfaces, collaborating with product and security teams to deliver scalable enterprise solutions.

Qualifications

• 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 DevOps.
• 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.

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 DevOps 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, DevOps engineers, security teams, and other technical teams throughout the development lifecycle.
• Translate business requirements into secure, scalable, measurable, and maintainable technical solutions.

Skills

Python

SQL

Full-stack development

AI/ML engineering

MLOps

CI/CD

Azure DevOps

Communication

Cross-functional collaboration

Education

Bachelor's degree in Computer Science, Data Science, Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or related

Master's degree or higher in Computer Science, Data Science, AI, ML, Biomedical Engineering, Engineering, or related

Tools

Azure DevOps

Vertex AI

AWS Bedrock

Amazon SageMaker

BigQuery

Snowflake

OpenSearch

Cloud Run

Docker

Airflow

Terraform

Job description

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/DevOps 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 DevOps 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, DevOps engineers, security teams, and other technical teams throughout the development lifecycle.
• Translate business requirements into secure, scalable, measurable, and maintainable technical solutions.

Required Qualifications

• 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 DevOps.
• 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.

Experience with several of the following technologies is preferred:

• Azure DevOps
• Vertex AI
• AWS Bedrock
• Amazon SageMaker
• BigQuery
• Snowflake
• OpenSearch
• Cloud Run
• Docker
• Airflow
• Terraform
• Comparable cloud, AI/ML, MLOps, and DevOps technologies

Preferred Experience

• Experience developing AI solutions using healthcare, clinical, claims, life sciences, regulatory, or other complex enterprise data.
• Experience taking AI/ML solutions from prototype through production deployment and ongoing operational support.
• Experience working in environments with significant security, privacy, compliance, and data governance requirements.

Education

• 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 Computer Science, Data Science, Artificial Intelligence, Machine Learning, Biomedical Engineering, Engineering, or a related field.

• Must pass a drug test and background check once offered position*

For those that join the team, we offer competitive compensation and benefits including medical, dental, vision, and retirement.

Check out all we have to offer and how you can become part of the Horizontal Talent Team.

The pay range for this role is $51 - $89 per hour based on qualifications and experience.