AI & Data Engineering Manager
Boston MA, United States
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athenahealth
Join 150K providers on the largest connected network in healthcare. See how we’re making connections that improve patient outcomes & clinician experiences.Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.
AI & Data Engineering Manager (Lead Member of Technical Staff- LMTS)
Position Summary
This position requires expertise in designing, developing, debugging, and maintaining AI-powered applications and data engineering workflows for both local and cloud environments. The role involves working on large-scale projects, optimizing AI/ML pipelines, and ensuring scalable data infrastructure.
As a LMTS, you will be responsible for building Generative AI (GenAI) capabilities, building data pipelines for AI model training, and deploying scalable AI-powered microservices. You will collaborate with other AI/ML, Data Engineering, DevOps, and Product teams to deliver impactful solutions that enhance our products and services.
Preferred qualifications include experience with retrieval-augmented generation (RAG), fine-tuning pre-trained LLMs, AI model evaluation, data pipeline automation, and optimizing cloud-based AI deployments.
Responsibilities
AI-Powered Software Development & API Integration
- Develop AI-driven applications, microservices, and automation. Build and maintain Python based AI services using lang Chain and CrewAI.
- Integrate and optimize OpenAI APIs (GPT models, Embeddings, Function Calling), hugging Face, LangChain, and implement Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval and classification, agentic AI workflows
- Deploy AI-powered applications using AWS Lambda, Kubernetes, Docker, CI/CD pipelines
Data Engineering & AI Model Performance Optimization
- Experience with building and optimizing scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake.
- Experience in assessing AI models using model scoring, fine tuning embeddings and enhance similarity search for retrieval augmented applications
- Experience on enhancing AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings).
Microservices, APIs & Security
- Design and develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT authetication, and API rate limiting.
- Implement AI-powered logging, observability, and monitoring to track data pipelines, model drift, and inference accuracy, ensuring compliance with AI governance and security best practices.
AI & Data Engineering Collaboration
- Work with AI/ML, Data Engineering, and DevOps teams to optimize AI model deployments, data pipelines, and real-time/batch processing for AI-driven solutions.
- Engage in Agile ceremonies, backlog refinement, estimate task accurately, drive incremental release of AI features, brainstorm different technical approaches to provide solutions in areas like fraud detection, claims processing, and intelligent automation.
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).
Mentorship & Knowledge Sharing
- Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions.
Education & Experience Required
- 10-14 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions.
- Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles.
- Bachelor’s Degree or equivalent in Computer Science, Engineering, Data Science, or a related field.
- Proficiency in full-stack development with expertise in Python (preferred for AI)
- Experience with structured & unstructured data: SQL, NoSQL, Big Data, Vector Databases and AI data pipelines
- Familiarity with Cloud & AI Infrastructure such as AWS, Azure, Kubernetes, Docker, CI/CD
- Experience with GenAI Frameworks & Tools: OpenAI API, Hugging Face Transformers, TensorFlow, LangChain, LlamaIndex, CrewAI.
- Experience in LLM deployment, retrieval-augmented generation (RAG), and AI search optimization.
- Experience in AI model evaluation (BLEU, ROUGE, BERT Score, cosine similarity) and responsible AI deployment.
- Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams.
- Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI adoption.
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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AI governance API Development APIs AWS Azure BERT Big Data CI/CD Classification Computer Science Data pipelines DevOps Docker Engineering FAISS Generative AI GPT Kafka Kubernetes Lambda LangChain LLMs Machine Learning Microservices ML infrastructure Model deployment Model inference Model training NoSQL OpenAI Pandas Pinecone Pipelines Privacy PySpark Python RAG Responsible AI SDLC Security Snowflake Spark SQL TensorFlow Transformers Unstructured data
Perks/benefits: Career development Health care Team events
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