AI Platform Engineer — GenAI & MLOps Specialist

RepliGen Corporation; Waltham (MA); On-site; USD 130,000 - 160,000; Full time

Benefits offered by this job

Paid time off

Health/Dental/Vision insurance

Retirement benefits

Flexible spending accounts

Job summary

Repligen Corporation is seeking an AI Engineer to drive enterprise-scale AI by designing reusable components, starter kits, and pattern-driven software for the Data Platform. You will help orchestrate multi-agent AI systems and governance across data workflows, enabling reliable, scalable AI solutions.

Based in the United States, this role emphasizes building scalable Python services, deploying on cloud platforms, and working with data teams to advance GenAI/LLM capabilities while maintaining

Qualifications

• 3+ years of experience with AI technologies, particularly GenAI, LLM, Agentic AI, or MLOps, and delivering enterprise-scale, production-grade solutions.
• Hands-on experience building agentic AI systems, including multi-agent workflows, orchestration, and tool integration using frameworks such as AutoGen or CrewAI and failure handling.
• Experience deploying and scaling AI solutions on platforms including Azure AI Foundry, Copilot Studio, or Google Vertex AI.

Responsibilities

• Build and orchestrate multi-agent AI systems across complex business workflows.
• Implement and refine prompt engineering strategies, including prompt chaining, evaluation, and guardrails.
• Develop scalable APIs and microservices to expose AI capabilities across systems and applications.

Skills

GenAI

LLM apps

MLOps

Agentic AI

API development

Python

Education

Bachelor's degree in Computer Science

Job description

Repligen Corporation is seeking an AI Engineer to drive enterprise-scale AI by designing reusable components, starter kits, and pattern-driven software for the Data Platform. You will help orchestrate multi-agent AI systems and governance across data workflows, enabling reliable, scalable AI solutions.

Based in the United States, this role emphasizes building scalable Python services, deploying on cloud platforms, and working with data teams to advance GenAI/LLM capabilities while maintaining