Senior Applied AI Engineer - Production ML & LLM Apps

Evolution USA; Boston (MA); On-site; USD 140,000 - 210,000; Full time

Job summary

Evolution USA is seeking a Senior Applied AI Engineer to design, deploy, and scale AI-powered solutions in production across cross-functional teams. This is not a pure research role.

You'll own projects from discovery through delivery, work directly with end users, and help translate complex AI concepts into real-world outcomes. The role focuses on large language models, agentic systems, and governance while collaborating with customers and stakeholders.

Qualifications

• Advanced degree (Masters or PhD) in CS/AI or a quantitative field.
• Strong experience building and deploying production AI/ML systems.
• Experience with LLMs, agentic workflows and AI evaluation frameworks.

Responsibilities

• Designing and deploying AI and machine learning solutions in production environments
• Building agentic AI systems and LLM-powered applications
• Developing evaluation, testing and governance frameworks for AI systems
• Working with structured and unstructured data sources
• Partnering directly with technical and non-technical stakeholders to define requirements and deliver solutions
• Contributing to architecture decisions and technical strategy
• Collaborating closely with software engineers, data specialists and domain experts
• Taking ownership of projects from discovery through delivery

Skills

Production AI/ML systems

LLMs

Agentic AI workflows

AI evaluation frameworks

Data processing pipelines

Cross-functional collaboration

Education

Master's degree in CS/AI/Data Science

Tools

AI orchestration frameworks

Cloud platforms

Python & ML frameworks

Job description

Evolution USA is seeking a Senior Applied AI Engineer to design, deploy, and scale AI-powered solutions in production across cross-functional teams. This is not a pure research role.

You'll own projects from discovery through delivery, work directly with end users, and help translate complex AI concepts into real-world outcomes. The role focuses on large language models, agentic systems, and governance while collaborating with customers and stakeholders.