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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/LLM Engineer - **Company:** Matlen Silver - **Location:** Charlotte, NC, United States (Remote available) - **Salary:** $114,400.0 - $135,200.0 - **Contract:** Internship / Graduate position - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Databases, Information Engineering, Data Files, Data Retrieval, Distributed Systems, Interoperability, Python (Programming Language), Oracle (Applications), Performance Tuning, SQL Databases, Systems Architecture, Systems Integration, Management of Software Versions, AI Infrastructure, Enterprise Software Applications, Chatbots, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Kubernetes, Information Technology, Low Latency, Machine Learning Operations, Serverless Computing, Web Api - **Published:** May 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4c6892a1a4890f99 ## About the Role Do you have experience in Tooling?, * Hands-on experience building production-grade RAG pipelines and agentic AI systems. * Strong experience with LLM fine-tuning, model adaptation, or custom inference workflows. * Deep understanding of at least one LLM orchestration framework such as: * LangChain * LlamaIndex * Similar orchestration frameworks * Strong Python development and API engineering experience. * Ability to clearly explain: * System architecture decisions * Tool/framework selection * Dataset preparation * Evaluation methodologies * Deployment and productionization strategies * Experience working on AI/ML projects such as: * Chatbots * Financial AI applications * Intelligent document/query systems Nice-to-Have Skills * Experience integrating LLMs with relational or structured databases. * Familiarity with vector databases and embedding stores such as: * Pinecone * Milvus * Weaviate * Oracle vector/embedding capabilities * Knowledge of: * Prompt engineering * Retrieval augmentation * LLM safety * Hallucination mitigation * Guardrail implementation * Experience with cloud infrastructure, model hosting, and monitoring in distributed environments. * Exposure to Kubernetes, serverless architectures, and AI infrastructure cost optimization. * Java experience is a plus for interoperability with enterprise systems. Preferred Background * Banking, financial services, fintech, or enterprise AI environments. * Strong academic background in Computer Science, AI/ML, Data Science, or related fields. * Candidates with standout internships, research, or hands-on AI projects are highly encouraged to apply. ## Description Job Description - AI/LLM Engineer (RAG & Agentic Systems) We are seeking a highly motivated AI/LLM Engineer to join a growing team focused on building next-generation generative AI solutions within the banking and financial services domain. This role will focus on designing and productionizing Retrieval-Augmented Generation (RAG) pipelines, agentic AI systems, and LLM-powered applications that interact with financial and structured enterprise data. The team is open to strong early-career candidates, including recent graduates with exceptional academic backgrounds, internships, or impactful AI/ML projects., * Design, extend, and optimize RAG pipelines, retrieval strategies, embedding workflows, and semantic search capabilities. * Build and productionize agentic AI architectures that orchestrate across: * RAG workflows * Structured SQL/data retrieval * External APIs and downstream actions (e.g., report/PPT generation) * Fine-tune and evaluate LLMs using model adaptation techniques, prompt engineering, and inference optimization. * Implement model safety mechanisms, guardrails, hallucination mitigation, and response validation strategies. * Develop and maintain APIs, endpoints, and tooling for model serving, observability, monitoring, and versioning. * Partner with SQL/data engineering teams to securely integrate structured enterprise data into LLM workflows. * Design reusable retrieval templates and interfaces for enterprise-scale AI applications. * Implement testing frameworks and monitoring for: * Latency * Accuracy * Hallucination rates * Cost efficiency * Retrieval quality * Participate in architecture and vendor-selection discussions focused on scalability, performance, and cost optimization. ## Related Videos - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Web APIs you might not know about](https://www.wearedevelopers.com/videos/281-web-apis-you-might-not-know-about) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Beyond the Hype: Building Trustworthy and Reliable LLM Applications with Guardrails](https://www.wearedevelopers.com/videos/1594-beyond-the-hype-building-trustworthy-and-reliable-llm-applications-with-guardrails) - [Project Fugu: Extending the web](https://www.wearedevelopers.com/videos/832-project-fugu-extending-the-web) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [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) - [Who Owns Your Content in the Age of LLMs?](https://www.wearedevelopers.com/magazine/610-who-owns-your-content-in-the-age-of-llms) - [Got AI ideas but no money? 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