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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/LLM Engineer - **Company:** CVS Health - **Location:** United States - **Experience:** Expert - **Salary:** $101,970.0 - $203,940.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Computer Programming, Software Debugging, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, MongoDB, Natural Language Processing, Standard Sql, Search Technologies, Software Construction, Data Logging, Data Processing, Google Cloud, Cloud Platform System, Flask (Web Framework), Large Language Models, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Fastapi, Pandas, Kubernetes, Information Technology, Machine Learning Operations, Api Design, Restful APIs, Automation Anywhere, Docker, Microservices - **Published:** August 15, 2026 - **Apply:** https://www.dice.com/job-detail/4e9f6ead-b1f0-4d05-8ff7-e42b07bbf42b ## About the Role * 5+ years expereince * Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience. * Strong programming experience in Python and familiarity with software engineering best practices. * Hands-on experience building production-grade AI/ML systems, not just prototypes. * Experience working with Large Language Models (LLMs) and APIs. * Solid understanding of: + Natural Language Processing (NLP) fundamentals + Machine learning concepts (training, evaluation, overfitting, bias) * Practical experience with: + Retrieval-Augmented Generation (RAG) systems + Prompt engineering and prompt optimization + Embeddings and vector search * Experience designing and implementing APIs, microservices, or distributed systems. * Familiarity with model evaluation techniques and performance metrics. * Strong debugging and problem-solving skills in complex systems., * Experience with LLM platforms such as OpenAI, Anthropic, Google Vertex AI, or similar. * Familiarity with orchestration frameworks like LangChain, LlamaIndex, Semantic Kernel, or equivalent. * Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, MongoDB Atlas Vector Search). * Knowledge of MLOps practices, including CI/CD pipelines for AI systems. * Experience deploying solutions in cloud environments (e.g., AWS, Azure, Google Cloud Platform). * Exposure to agent-based architectures or multi-step AI workflows. * Experience in financial services enterprise environments (or similar data-intensive industries). * Experience with evaluation frameworks and benchmarking for LLMs. ## Description As a key member of a cross-functional team, you will collaborate with business stakeholders to translate business requirements into reliable, explainable, and production-ready AI solutions. You will play a critical role in shaping enterprise AI capabilities by ensuring solutions are secure, responsible, and optimized for real-world performance. * Design and implement LLM-powered applications that support complex, text-based reasoning and decision workflows. * Develop and refine chain-of-thought-style reasoning approaches and structured prompt patterns to improve model accuracy and interpretability. * Architect and build Retrieval-Augmented Generation (RAG) systems leveraging embeddings, vector search, and hybrid retrieval strategies. * Create, evaluate, and optimize prompt engineering frameworks, including reusable templates, prompt libraries, and testing methodologies. * Implement monitoring, logging, and feedback loops for continuous improvement of AI systems. * Ensure compliance with security, governance, and Responsible AI principles. * Partner with product and analytics teams to rapidly prototype and iterate AI-driven features. Tools & Technologies * Programming: Python (primary), SQL * LLM Platforms: OpenAI, Anthropic, Google Vertex AI * Frameworks: LangChain, LlamaIndex, Semantic Kernel * Vector Databases: Pinecone, Weaviate, FAISS, MongoDB Atlas Vector Search * Data Processing: Spark, Pandas * APIs & Services: FastAPI, Flask, REST/gRPC * Cloud Platforms: AWS, Azure, Google Cloud Platform (Google Cloud Platform) * DevOps & MLOps: Docker, Kubernetes, CI/CD tools * Monitoring & Evaluation: Prompt evaluation tools, logging frameworks, observability platforms ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [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) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## 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) - [Got AI ideas but no money? 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