> Markdown version of [/jobs/ext/185860-ai-engineer-ii](https://www.wearedevelopers.com/jobs/ext/185860-ai-engineer-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI Engineer II

- **Company:** Repligen Corporation
- **Location:** Waltham, MA, United States
- **Experience:** Expert
- **Salary:** $130,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Microsoft Azure, Encodings, Information Systems, Continuous Integration, Information Engineering, Data Retrieval, Software Debugging, Digital Architecture, Distributed Systems, Graph Database, Machine Learning, Tensorflow, Search Technologies, Software Engineering, Solution Deployment Descriptor, Web Application Frameworks, Data Processing, Google Cloud, Enterprise Software Applications, Cloud Platform System, Data Ingestion, Pytorch, Retrieval-Augmented Generation, System Availability, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Generative AI, Indexer, Backend, Scikit Learn, Information Technology, Machine Learning Operations, Virtual Agents, Api Design, Restful APIs, Terraform, Data Pipelines, Databricks, Microservices
- **Published:** May 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=604e545272709db4

## About the Role

Do you have experience in AI?, Do you have a Bachelor's degree?, * Bachelor's degree in computer science, Statistics, Data Science, Information Systems or related field

 * 5+ 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 scikit-learn.
 * Expertise in Generative AI and LLM application development using OpenAI and Anthropic APIs, including:
 + Advanced prompt engineering and optimization techniques
 + Design and implementation of Retrieval-Augmented Generation (RAG) architectures
 + Embeddings, semantic search, and contextual retrieval strategies
 + Experience with vector databases such as Pinecone, FAISS, Weaviate or AI data cloud platform such as Databricks or Snowflake
 * Strong background in API development, microservices architecture, and distributed systems, enabling scalable AI solution deployment
 * Experience with knowledge graphs, graph databases, or hybrid retrieval systems to enhance contextual reasoning and data relationships
 * Proficiency in Python programming

Experience deploying using CI/CD, infrastructure as code (Terraform), monitoring, debugging & managing AI/ML solutions in cloud environments AWS, Azure & GCP

## Description

* 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
 * Own the administration, provisioning, and ongoing optimization of the enterprise AI tool ecosystem, ensuring secure access controls and optimal functionality for development teams
 * 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


## Related Videos

- [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock)
- [Optimizing Discovery: PostgreSQL's Role in Transforming GetYourGuide's Search](https://www.wearedevelopers.com/videos/1647-optimizing-discovery-postgresql-s-role-in-transforming-getyourguide-s-search)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software)
- [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean)
- [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow)

## Related Articles

- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)
- [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)