M

MCI

Provides BPO call center outsourcing services

RAG Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeUnited StatesNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's Degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, Software Engineering, or a related field is required.
  • At least 3 years of experience in software engineering, AI engineering, machine learning, or information retrieval is required.
  • Strong proficiency in Python and experience developing production-grade applications are required.
  • Experience building APIs, microservices, or cloud-native applications is required.
  • A solid understanding of Large Language Models (LLMs) and Generative AI concepts is required.
  • Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions is required.
  • An understanding of embeddings, vectorization techniques, and semantic search methodologies is required.
  • Experience working with structured and unstructured data sources is required.
  • Knowledge of data ingestion, indexing, and retrieval pipelines is required.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform is required.
  • Strong analytical, troubleshooting, and problem-solving skills are required.
  • Excellent communication and stakeholder engagement abilities are required.
  • Must be authorized to work in the country where the job is based.
  • Must be willing to submit to a Level II background and/or security investigation with fingerprinting, subject to the program and location.
  • Must be willing to submit to drug screening, subject to the program and location; this does not apply in Canada.

Responsibilities

  • Design and maintain Retrieval-Augmented Generation solutions that provide accurate and context-aware responses.
  • Build document ingestion, indexing, and retrieval pipelines.
  • Develop enterprise knowledge repositories and search frameworks.
  • Implement semantic search capabilities across structured and unstructured data.
  • Design scalable architectures supporting AI-powered knowledge retrieval.
  • Optimize retrieval performance and relevance across AI applications.
  • Implement and manage vector databases and embedding pipelines.
  • Improve retrieval quality through tuning and evaluation.
  • Optimize latency, scalability, and search effectiveness.
  • Maintain data quality and knowledge management standards.
  • Support the integration of retrieval systems with AI applications.
  • Collaborate with AI engineers and product teams on solution design.
  • Integrate retrieval services with Large Language Models.
  • Develop APIs and services that support AI workflows.
  • Ensure reliable access to enterprise knowledge sources.
  • Maintain operational excellence across RAG environments.
  • Monitor retrieval accuracy and system performance.
  • Implement governance and data security controls.
  • Troubleshoot retrieval and indexing issues.
  • Maintain documentation and operational procedures.
  • Drive continuous improvement in retrieval technologies and methodologies.
  • Evaluate emerging retrieval frameworks and search technologies.
  • Research new approaches to knowledge management and retrieval optimization.
  • Recommend enhancements to improve user experience and AI performance.
  • Contribute to AI architecture and innovation initiatives.

Desired Qualifications

  • Experience with Pinecone, Weaviate, Milvus, Chroma, or similar vector databases is desirable.
  • Experience with LangChain, LlamaIndex, Haystack, or related frameworks is desirable.
  • Knowledge of knowledge management and enterprise search platforms is desirable.
  • Exposure to MLOps practices and AI deployment pipelines is desirable.
  • Experience building conversational AI or chatbot solutions is desirable.
  • Familiarity with containerization technologies such as Docker and Kubernetes is desirable.
  • An understanding of AI governance, security, and compliance requirements is desirable.
  • Experience working within Agile development environments is desirable.

About the Company

MCI

Provides BPO call center outsourcing services

MCI provides business process outsourcing and call center services to a wide range of clients in both B2B and B2C markets. The company handles customer interactions and back-office tasks to improve customer experience, boost efficiency, and reduce client costs. With operations in seven countries and a global team of over 5,000 associates, MCI delivers support at scale across multiple languages and industries. Growth comes from organic expansion and acquisitions, assembling a family of firms that offer complementary services under a single umbrella. MCI’s main differentiators are its global reach, long-term client relationships, and focus on measurable outcomes such as higher customer satisfaction and lower operating expenses. The company’s goal is to help clients streamline their customer-facing processes and back-office operations while driving cost savings and revenue improvements.

Company size
1,001-5,000
Company stage
Early VC
Total funding
$4.2M
Headquarters
Iowa City, IA
Founded
2015

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