Job Summary
Make a global impact—join Repligen.
We’re united by a mission to inspire advances in bioprocessing as a preferred partner in the production of biologic drugs that improve human health worldwide. No matter your role or background, at Repligen, you will play a key part in shaping some of the most innovative and life-changing therapies in the world. We foster a culture of purpose, collaboration, and shared success—where every voice matters and every contribution drives progress. Join us!
Role Overview
We are seeking a unique individual with a passion for AI technology who can help to drive forward enterprise-wide scale AI adoption. Repligen is in a transformational period where we are accelerating our capabilities, technologies, and data to augment our scientific mission.
As an AI Engineer, you will unlock and accelerate AI by designing the reusable components, starter kits, and opinionated developer first patterns for the Platform. This person will be a key contributing member of the Data Platform, driving forward the deployment and management of Repligen’s enterprise platform for data & AI. This is a critical role for a highly skilled AI engineer who is passionate about building innovative solutions. This role operates at the platform level, shaping how teams build AI on the platform by turning best practices into predictable and repeatable patterns embedding governance into code, and reducing time to value for new use cases. You will be at the heart of our AI initiatives, ensuring that we maintain engineering excellence while delivering impactful products. Key Responsibilities
Build and orchestrate multi-agent AI systems using state-of-the-art platforms, enabling agents to collaborate on task planning, data retrieval, and execution across complex business workflows.
Implement and continuously refine prompt engineering strategies, including prompt chaining, evaluation, and guardrails to improve accuracy and reliability
Build and maintain RAG (Retrieval-Augmented Generation) pipelines, including Data ingestion and indexing, Embedding generation, Retrieval optimization & Response grounding and validation
Development of scalable backend services using Python frameworks for data processing
Design and manage embedding pipelines and vector search infrastructure using tools such as Pinecone, FAISS, Weaviate, Databricks or Snowflake
Integrate LLM capabilities from platforms like OpenAI, Anthropic, and Microsoft into enterprise applications
Build and maintain scalable APIs and microservices to expose AI capabilities across systems and applications
Collaborate with data engineering and platform teams to ensure reliable data pipelines and access to high-quality data sources
Deploy, monitor, and optimize AI solutions in cloud environments (Azure, AWS, GCP), ensuring performance, scalability, and cost efficiency
Implement evaluation frameworks and monitoring for LLM outputs, including quality metrics, drift detection, and feedback loops
Troubleshoot and resolve issues in distributed AI systems, ensuring high availability and reliability
Partner with business stakeholders to translate requirements into AI-driven solutions and automation opportunities
Document architecture, design decisions, and best practices to support scalability and team adoption
Required Qualifications
Bachelor’s degree in computer science, Statistics, Data Science, Information Systems or related field
3+ years of experience with AI technologies, particularly GenAI, LLM, Agentic AI, or MLOps, and delivering enterprise-scale, production-grade solutions
Hands-on experience in 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
Hands-on experience in machine learning and deep learning frameworks such as TensorFlow, PyTorch, and…