> Markdown version of [/jobs/ext/3785614-software-development-engineer-ai](https://www.wearedevelopers.com/jobs/ext/3785614-software-development-engineer-ai). 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). --- # Software Development Engineer AI - **Company:** CVS Health - **Location:** Home, PA, United States (Remote available) - **Experience:** Expert - **Salary:** $83,430.0 - $203,940.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Computer Programming, Continuous Integration, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, MongoDB, Natural Language Processing, OpenAI, Search Technologies, Software Construction, Software Engineering, SQL Databases, Data Logging, Pinecone, Data Processing, Google Cloud, Cloud Platform System, LangChain, Flask (Web Framework), Large Language Models, Prompt Engineering, Apache Spark, Google Vertex AI, Model Validation, Llamaindex, Generative AI, Agentic-AI, Fastapi, Pandas, Kubernetes, Information Technology, Weaviate, Machine Learning Operations, FAISS, Api Design, Restful APIs, Semantic Kernel, Automation Anywhere, Docker, Microservices - **Published:** October 16, 2026 - **Apply:** https://www.juju.com/job/1_cvs4-R1047559 ## About the Role You will play a critical role in shaping enterprise AI capabilities by ensuring solutions are secure, responsible, and optimized for real-world performance. **Required Qualifications** + 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. **Preferred Qualifications** + 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, GCP). + 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. **Tools and 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 (GCP) + DevOps & MLOps: Docker, Kubernetes, CI/CD tools + Monitoring & Evaluation: Prompt evaluation tools, logging frameworks, observability platforms **Education** ** ** Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience. **Anticipated Weekly Hours** 40 **Time Type** Full time **Pay Range** The typical pay range for this role is: $83,430.00 - $203,940.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls.