Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.
Responsibilities may include, but are not limited to:
50% [Primary Function] Technical Execution
- Contribute to accurate, unambiguous technical design specifications, including GenAI system integration and AI-enhanced workflows.
- Deliver customer value in the form of high-quality AI-powered software components and services, ensuring adherence to security, performance, longevity, and AI-driven automation best practices.
- Estimate the size of development tasks in story points, considering LLM inference latency and AI API rate limits.
- Understand and follow coding conventions, architectures, and best practices for GenAI-powered applications, LLM prompt engineering, and RAG (Retrieval-Augmented Generation) models.
- Write, debug, and deploy code to production, ensuring timely fixes for GenAI-based APIs, embeddings, and AI-driven microservices.
- Integrate and optimize OpenAI, Azure OpenAI, Hugging Face, LangChain, and LlamaIndex into enterprise applications.
- Leverage vector databases (Pinecone, FAISS, ChromaDB) for similarity search and AI retrieval pipelines.
- Adhere to Definition of Done (DOD) as part of the sprint, including:
- Unit tests, functional testing
- LLM performance benchmarking (BLEU, ROUGE, cosine similarity)
- AI model validation & API response optimization (temperature, top-k, max tokens)
- Code reviews, bug fixes, documentation
- Adherence to AI governance & responsible AI practices
30% Contributions to the Team
- Learn domain-specific AI applications, including GenAI capabilities in automation, search, and AI-assisted decision-making.
- Take ownership of AI-enhanced product features, ensuring continuous model improvement and fine-tuning strategies.
- Contribute to agile ceremonies with a focus on AI-driven solutions and optimizations.
- Volunteer for GenAI-focused backlog items, such as:
- RAG model refinement
- Prompt engineering for better accuracy
- LLM evaluation and response optimization
- Participate in scrum meetings (daily stand-ups, sprint planning, readouts, retrospectives) with a focus on AI model iteration and feature scaling.
- Drive self-organization in AI workflows, ensuring GenAI is used effectively across teams.
10% Cross functional Coordination and Communication
- Work collaboratively across Technology, Product, AI/ML, and DevOps teams to align AI-driven enhancements with business goals.
- Build strong relationships with AI engineers, data scientists, and cloud architects to optimize LLM-based applications.
- Ensure AI compliance with security, ethical AI policies, and privacy standards (HIPAA, GDPR, SOC2, AI governance best practices).
10% Mentorship of Others
- Train and mentor developers on GenAI integration, AI API usage, embeddings, and vector search optimizations.
- Guide the team on LLM prompt engineering, RAG model improvements, and API latency optimization.
- Encourage adoption of AI-enhanced developer workflows (e.g., Copilot, AI-assisted code generation, AI-powered testing).
Education, Experience, & Skills Required
- 5-10 years of experience in an engineering role, with exposure to AI/ML concepts.
- Experience in an Agile environment preferred.
- Bachelor’s Degree or equivalent in Computer Science, Engineering, or related field.
- Strong software engineering experience, including AI model integration and GenAI API workflows.
- Knowledge of modern programming language: Python (preferred for AI applications)
- Familiarity with Unix/Linux, Big Data, SQL, NoSQL, and AI data pipelines.
- Experience with AI frameworks and APIs such as OpenAI GPT, Hugging Face Transformers, LangChain, LlamaIndex.
- Exposure to retrieval-augmented generation (RAG), embeddings, and AI search optimization techniques.
- Understanding of vector databases (FAISS, Pinecone, ChromaDB) and similarity search models.
- Proficiency in cloud-based AI deployments (AWS or Azure OpenAI).
- Strong grasp of GenAI model evaluation techniques (BLEU, ROUGE, BERT Score, cosine similarity metrics).
Behaviors & Abilities Required:
- Ability to design and implement AI-powered solutions that improve software functionality.
- Problem-solving mindset to debug and optimize AI-generated responses.
- Ability to collaborate across AI, DevOps, and software engineering teams for seamless AI model integration.
- Experience in AI-driven feature development, from prompt engineering to embedding optimization.
- Ability to assess AI-generated content for bias, accuracy, and compliance.
- Strong analytical skills to measure AI model performance and recommend improvements.
- Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI deployment.
About Athenahealth
Our vision:
In an industry that becomes more complex by the day, we stand for simplicity. We offer IT solutions and expert services that eliminate the daily hurdles preventing healthcare providers from focusing entirely on their patients — powered by our vision to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.
Our company culture:
Our talented
employees — or athenistas, as we call ourselves — spark the innovation and passion needed to accomplish our vision. We are a diverse group of dreamers and do-ers with unique knowledge, expertise, backgrounds, and perspectives. We unite as mission-driven problem-solvers with a deep desire to achieve our vision and make our time here count. Our award-winning culture is built around shared values of inclusiveness, accountability, and support.
Our DEI commitment:
Our vision of accessible, high-quality, and sustainable healthcare for all requires addressing the inequities that stand in the way. That's one reason we prioritize diversity, equity, and inclusion in every aspect of our business, from attracting and sustaining a diverse workforce to maintaining an inclusive environment for athenistas, our partners, customers and the communities where we work and serve.
What We Can Do For You
Along with health and financial benefits, athenistas enjoy perks specific to each location, including commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative
workspaces
—
some offices even welcome dogs.
We also encourage a better work-life balance for athenistas with our flexibility. While we know in-office collaboration is critical to our vision, we recognize that not all work needs to be done within an office environment,
full-time. With consistent communication and digital collaboration tools, athenahealth
enables
employees to find a balance that feels fulfilling and productive for each individual situation.
In addition to our traditional benefits and perks, we sponsor events throughout the year, including book clubs, external speakers, and hackathons. We provide athenistas with a company culture based on learning, the support of an engaged team, and an inclusive environment where all employees are valued.
Learn more about our culture and benefits here: athenahealth.com/careers
https://www.athenahealth.com/careers/equal\-opportunity
