Member of Technical Staff - LLM/AI

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:

80% [Primary Function] Technical Execution

• Contribute to accurate, unambiguous technical design specifications with appropriate detail, including GenAI-based system integration.
• Deliver customer value in the form of high-quality software components and AI-powered services while ensuring adherence to security, performance, longevity, and AI model integration best practices.
• Estimate the size of development tasks in story points.
• Understand and follow coding conventions, AI model integration architectures, and best practices for working with LLMs (Large Language Models).
• Write, debug, and deploy code to production, ensuring timely fixes and optimizations for GenAI-powered applications.
• Adhere to Definition of Done (DOD) as part of the sprint, including unit tests, functional testing, code reviews, API performance validation, AI model evaluation, and prompt tuning.
• Implement and optimize GenAI-based workflows (e.g., OpenAI APIs, LangChain, vector databases for RAG, AI-driven automation).

10% Contributions to the Team

• Learn the domain knowledge for the assigned area, including how GenAI solutions can improve product offerings.
• Take ownership of GenAI-powered features and AI-driven automation post-release, ensuring continuous improvement.
• Participate in AI use case discussions, including LLM fine-tuning, retrieval-augmented generation (RAG), prompt engineering, and AI-based automation.
• Contribute to agile ceremonies to improve team performance.
• Volunteer for work in the backlog, including GenAI model integration tasks, and commit to high-quality delivery.
• Participate in scrum meetings (daily stand-ups, sprint planning, readouts, and retrospectives).
• Help determine how GenAI is leveraged effectively in collaboration with cross-functional teams.

5% Cross functional Coordination and Communication

• Work collaboratively across the Technology, Product, and AI/ML teams to ensure alignment toward GenAI integration goals.
• Build strong relationships with AI engineers, data scientists, and cross-functional team members to leverage AI capabilities in products.

5% Mentorship of Others

• Share knowledge on GenAI best practices, AI integration strategies, and API-based AI services with team members.
• Participate in AI/ML discussions, helping others learn how to integrate and optimize GenAI models in software applications.

Education, Experience, Skills Required:

• 2-4 years of experience in a software engineering role, with exposure to AI/ML concepts.
• Familiarity with working in an Agile environment preferred.
• Bachelor s Degree or equivalent in Computer Science, Engineering, or a related field.
• Software engineering experience, with exposure to AI model integration and generative AI frameworks.
• Knowledge of modern programming language such as: Python - preferred for AI applications
• Familiarity with Unix/Linux, Big Data, SQL, NoSQL, and modern data storage technologies.
• Experience with AI APIs and frameworks such as OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, and vector databases (FAISS, Pinecone, ChromaDB).
• Exposure to object-oriented programming, RESTful APIs, distributed computing, WebU, and modern JavaScript frameworks.
• Understanding of GenAI model deployment in cloud environments (AWS or Azure).
• Familiarity with AI model evaluation techniques, including embeddings, retrieval-augmented generation (RAG), and prompt engineering.

Behaviors Abilities Required:

• Ability to learn and adapt in a fast-paced environment, particularly in AI and GenAI integration.
• Ability to write performant, scalable, and maintainable code for AI-powered applications.
• Critical thinking skills to assess AI-generated outputs and improve model reliability.
• Problem-solving mindset to identify alternative methods of solving software engineering and AI-related challenges.
• Proven track record of delivering AI-integrated features while following best practices in software development.
• Ability to collaborate on AI-driven solutions, working with cross-functional teams, data scientists, and software engineers.
• Curiosity and willingness to explore new AI models, tools, and frameworks for enhancing software applications with GenAI capabilities.