athenahealth - Technical Staff Engineer - Artificial Intelligence/LLM

About the Role :

We are seeking a Member of Technical Staff specializing in Large Language Models (LLMs) and AI to join our engineering team. This role focuses on building, integrating, and deploying generative AI solutions into enterprise-grade software systems.

The ideal candidate brings strong software engineering fundamentals, hands-on experience with AI/ML frameworks, and the ability to design scalable, production-ready AI-powered applications.

Key Responsibilities :

- Design & Development : Develop, integrate, and optimize applications leveraging LLMs, generative AI frameworks, and vector databases.

- AI Integration : Implement APIs and SDKs from platforms such as OpenAI, Hugging Face, LangChain, and LlamaIndex into production systems.

- Prompt Engineering & RAG : Design, test, and optimize prompt strategies, embeddings, and retrieval-augmented generation workflows.

- Data Engineering : Work with structured/unstructured datasets, SQL/NoSQL systems, and modern storage solutions to prepare data pipelines for AI applications.

- Scalable Systems : Build performant, maintainable, and secure AI-enabled services with a focus on distributed computing and cloud-native deployments (AWS, Azure).

- Collaboration : Work closely with product managers, data scientists, and software engineers to deliver AI-powered features aligned with business goals.

- Evaluation & Monitoring : Apply AI model evaluation techniques to validate model performance, reliability, and fairness in real-world applications.

- Agile Practices : Contribute to sprint planning, code reviews, and CI/CD pipelines in a modern Agile development environment.

Required Skills & Experience

- Experience : 2 to 4 years in software engineering, with at least 1 year hands-on in AI/ML development and integration.

- Programming : Proficiency in Python (preferred for AI/ML), with additional experience in JavaScript/TypeScript for frontend or service integration.

- AI/ML Ecosystem : Practical experience with OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, FAISS, Pinecone, or ChromaDB.

- Cloud & Deployment : Familiarity with deploying GenAI applications in AWS or Azure environments.

- Data Systems : Knowledge of relational databases (SQL), NoSQL systems, and data pipelines for AI workloads.

- APIs & Frameworks : Strong understanding of RESTful APIs, microservices, and modern web frameworks.

- Software Engineering : Exposure to distributed computing, system design, and building production-grade software.

- Foundations : Bachelors degree (or higher) in Computer Science, Engineering, or a related technical field.