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athenahealth - Senior Technical Staff Engineer - Generative AI

athenahealth - Senior Technical Staff Engineer - Generative AI

athenaHealth Technology Private Limited.Chennai
18 days ago
Job description

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.
  • Bachelors 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.

    • (ref : hirist.tech)

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