AI Engineer II
Repligen Corporation
Waltham, MA, United States
3 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$130,000.0 - $200,000.0
Working hours
Regular working hours
Job source
Tech stack
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
+33 more
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
Job 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
Requirements
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
Benefits & conditions
Pulled from the full job description
- Retirement plan
- Paid time off
- Vision insurance
- Dental insurance
- Flexible spending account, Our mission is to inspire advances in bioprocessing as a trusted partner in the production of biologic drugs that improve human health worldwide. Focused on cost and process efficiencies, we deliver innovative technologies and solutions that help set new standards in bioprocessing. The estimated salary range for this role, based in the United States of America is $130,000-$200,000. Compensation decisions are dependent on several factors including, but not limited to an individual’s qualifications, location, internal equity, and alignment with market data. Additionally, employees are eligible to participate in one of our variable cash programs (bonus or commission) and eligible roles may receive equity as part of the compensation package. We offer a wide range of benefits such as paid time off, health/dental/vision, retirement benefits and flexible spending accounts. All compensation and benefits information will be confirmed in writing at the time of offer.
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