- Full-Stack Implementation: Develop and customize user-facing components, APIs, and workflow orchestrations to integrate Autonomize AI into customer EHRs and claims systems.
- Applied ML Engineering: Fine-tune and configure LLMs and machine learning models for specific customer use cases (e.g., Prior Authorization, CM Audit, or HEDIS reviews).
- DevOps & Deployment: Assist in the deployment of our platform across various environments (SaaS and VPC), ensuring high reliability and security compliance.
- Business Analysis & Discovery: Translate complex customer business requirements into technical specifications. You will help define the "Success Criteria" for each deployment.
- Education: B.S. or M.S. in Computer Science, Data Science, or a related technical field.
- Full-Stack Development: Proficiency in modern languages (Python preferred) and experience with web frameworks and API design (REST/GraphQL).
- Machine Learning: Foundational understanding of NLP, Large Language Models (LLMs), and data preprocessing. Experience with frameworks like PyTorch or TensorFlow is a plus.
- Infrastructure/DevOps: Exposure to cloud platforms (AWS/Azure/GCP) and containerization (Docker/Kubernetes).
- Analytical Mindset: Ability to act as a Business Analyst—asking the right questions to understand a customer’s "pain point" before writing a single line of code.
- Communication: Exceptional ability to explain technical AI concepts to non-technical healthcare stakeholders.
- Experience leading a team of developers, driving quality and deliverables through direction, mentoring and code reviews
- Experience working with stakeholders to translate business needs into actionable development requirements
- Familiarity with visualization libraries
- Familiarity with AI/ML, Data Analytics frameworks - PyTorch, Tensorflow, HuggingFace
- Familiarity with various databases like Postgres, Elasticsearch (ELK), or GraphDBs (neo4j, Tiger Graph etc)
- Exposure on OpenAI APIs.
- Worked on Kafka, ActiveMQ and/or REDIS
- A chance to make a real impact in the future of healthcare
- Autonomy, ownership, and the ability to chart your own growth path
- Competitive compensation and benefits
- 100% employer-paid health, vision, and dental insurance
- Retirement plans (401k), disability insurance, employee assistance programs
Skills Required
- B.S. or M.S. in Computer Science, Data Science, or a related technical field
- Proficiency in modern programming languages, preferably Python
- Experience with web frameworks and REST or GraphQL API design
- Foundational understanding of NLP, large language models, and data preprocessing
- Exposure to AWS, Azure, or GCP cloud platforms
- Exposure to Docker or Kubernetes containerization
- Ability to analyze customer pain points and translate business requirements into technical specifications
- Exceptional ability to explain technical AI concepts to non-technical healthcare stakeholders
- Experience with PyTorch or TensorFlow
- Experience leading developers through direction, mentoring, and code reviews
- Experience translating stakeholder needs into actionable development requirements
- Familiarity with visualization libraries
- Familiarity with PyTorch, TensorFlow, or Hugging Face AI and machine learning frameworks
- Familiarity with PostgreSQL, Elasticsearch, Neo4j, or TigerGraph
- Exposure to OpenAI APIs
- Experience with Kafka, ActiveMQ, or Redis
What We Do
Autonomize AI Agents & Copilots organize, contextualize and summarize unstructured data to reduce the administrative burden for healthcare knowledge workers to make data-driven decisions and improve patient outcomes. Our customers include health plans, providers and life sciences companies. Unlike generic AI systems retrofitted for healthcare, Autonomize deeply understands medical contexts, terminologies, and operational nuances. Our healthcare-focused AI Agents & Copilots augment knowledge work, drastically reducing administrative burden. Care management teams spend 78% less time per case, achieving an impressive 85% boost in case review efficiency. Prior authorization processes that traditionally take 20-30 minutes shrink to mere seconds, accompanied by an 80% reduction in manual errors, saving millions of dollars annually. Our AI Agents turn chaotic, unstructured healthcare data—clinical notes, PDFs, faxes, and claims—into structured, contextual information that informs decisions and actions. This has driven substantial real-world impact: organizations using Autonomize experience a 92% reduction in manual effort for care gaps and HEDIS chart reviews, dramatically improving compliance and STAR ratings. Autonomize AI is purpose-built for healthcare, transforming healthcare operations one workflow at a time through AI-native solutions that deliver immediate, scalable impact.
