Staff Software Engineer (AI Engineering)

Tebra; New York (NY); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Hybrid work model

Stock options

401k

Health insurance

Employer-funded HSA

Mentorship program

Job summary

Tebra is seeking a Staff Software Engineer on the Revenue Cycle Management team to lead the design, development, and adoption of AI-native capabilities across our billing and revenue cycle platform. You will drive architectural choices, implement production AI systems, and mentor engineers across teams.

In this role you will partner with product, design, data, and operations to translate complex healthcare workflows into reliable, scalable software using Java, Spring Boot, React, and cloud

Qualifications

• 8+ years of professional software engineering experience building scalable distributed systems.
• Hands-on with AI-native or AI-enabled production systems and backend services.
• Experience leading architecture, code reviews, and mentoring engineers.

Responsibilities

• Lead design, development, testing, and deployment of AI-powered services.
• Architect robust, scalable solutions meeting business requirements.
• Collaborate with product, design, data, and operations to translate workflows into software.
• Mentor junior engineers and drive engineering standards for reliability and observability.

Skills

Java

Spring Boot

Python

AI systems engineering

Distributed systems

Leadership

Tools

LangChain

LangGraph

LlamaIndex

PyTorch

Hugging Face Transformers

Vector databases

Job description

• The Revenue Cycle Management (RCM) team is seeking a Staff Software Engineer to lead the design, development, and adoption of AI-native capabilities across our billing and revenue cycle platform
• This role combines deep software engineering expertise with hands‑on experience building production AI systems. You will help transform how healthcare organizations manage billing, payments, claims, and operational workflows by applying Large Language Models (LLMs), intelligent automation, retrieval systems, and agentic AI architectures to solve real‑world business problems
• As a senior individual contributor, you will operate at the intersection of platform architecture, AI systems engineering, and business transformation. You will influence technical strategy across teams, design reusable AI capabilities, and establish engineering standards for building reliable, secure, and scalable AI-powered systems
• Your impact will come through technical leadership, architectural ownership, hands‑on implementation, and your ability to translate complex business challenges into intelligent software solutions that deliver measurable outcomes
• Identify and implement practical opportunities to embed AI into backend services and business workflows where it can improve efficiency, accuracy, or decision support
• Design and build production‑ready AI‑enabled services that combine application logic, APIs, and AI models to support real customer and operational use cases
• Integrate LLMs, ML models, and external AI services into existing systems using strong engineering patterns for reliability, observability, and maintainability
• Build workflows that use AI in a bounded, auditable way, with clear fallback behavior, evaluation, and human review where appropriate
• Partner with product, design, data, and operational teams to turn workflow pain points into scalable software solutions with measurable impact
• Lead Software Development: Design, develop, test, and deploy scalable and maintainable software applications using Spring Boot, Java, React, and cloud technologies
• Architect and Design: Collaborate with product managers, designers, and cross‑functional teams to architect robust and scalable solutions that meet business requirements. Provide input into the technical direction of the team and product
• Cloud Technology Expertise: Leverage experience with cloud platforms (AWS, Azure, Google Cloud, etc.) to design cloud‑native applications. Ensure that applications are optimized for scalability, reliability, and cost‑efficiency in a cloud environment
• Code Reviews & Mentorship: Conduct thorough code reviews, ensuring that the team adheres to best practices for clean, maintainable, and efficient code. Mentor junior and mid‑level engineers, fostering a culture of continuous learning and improvement
• Collaboration and Communication: Work closely with product and design teams to define requirements, deliver timely solutions, and provide technical expertise throughout the product lifecycle
• Performance and Optimization: Monitor and optimize the performance of applications. Identify bottlenecks and implement performance improvements across both frontend (React) and backend (Java/Spring Boot) layers
• Agile Development: Participate in Agile development processes, including sprint planning, daily standups, retrospectives, and backlog grooming. Contribute to defining and prioritizing work within the team
• Stay Current: Continuously research and apply emerging technologies and industry best practices to improve the development process and product quality

Benefits

• Competitive compensation packages
• Employee referral program
• Stock options
• Hybrid work model
• Equipment stipend when hired
• Monthly work‑from‑home subsidy
• Indoor‑outdoor workspaces
• Flexible, paid time off
• 10 paid holidays
• Employee recharge days
• Financial health tools
• Gympass
• Fun Express
• Annual fitness challenge
• Obé Fitness
• Competitive medical, dental, and vision insurance
• 401k
• Employer‑funded HSA
• Life and disability insurance
• Employee assistance program
• Accident insurance, critical illness insurance, legal & identity theft protection, pet discount program
• Mentorship program
• Professional development training
• Employee resource groups
• Dedicated DE&I
• Special events and speakers
• Community volunteer events
• Sponsored team events and sports
• Recognition Program

Production AI Experience: 2-3+ years of hands‑on experience designing, shipping, and maintaining production AI-enabled or AI-native applications (combining LLMs, core application logic, and business workflows)Collaboration: Impact‑driven mindset with excellent cross‑functional communication skills to bridge Engineering, Product, Design, and OperationsDomain Expertise: Prior background in Healthcare IT, Revenue Cycle Management (RCM), billing, claims processing, fintech, or similarly regulated, high-compliance transaction environments preferredAdvanced Agentic AI: Experience building autonomous, multi‑step agentic systems utilizing multi‑tier memory networks and recursive reasoning preferredDeep Data Retrieval: Hands‑on experience with vector databases, semantic search architectures, and enterprise knowledge graph construction preferredAdvanced ML Tooling: Exposure to PyTorch, Hugging Face Transformers, custom embedding models, fine‑tuning methodologies, or model serving optimizationAI Orchestration & Architecture: Practical experience with orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, CrewAI) and a deep understanding of RAG, tool calling, prompt engineering, context/state management, and human‑in‑the‑loop patternsProduction Safeguards & MLOps: Proven experience implementing enterprise AI guardrails, including real‑time observability, latency/cost monitoring, automated evaluation pipelines, and robust fallback mechanismsLeadership Pedigree: Past experience serving as a Founding Engineer, Principal Architect, or early‑stage platform lead driving organization‑wide AI/ML adoption frameworks preferredSystems Infrastructure & Data: Strong background in distributed systems, event‑driven architectures, asynchronous processing, and messaging platforms (e.g., Kafka)Experience & Seniority: 8+ years of professional software engineering experience building scalable distributed systems, with a track record of driving technical direction and architecture decisions without formal authorityCore Technical Stack: Absolute mastery of Java, Spring Boot, and Python for developing secure, high‑throughput, cloud‑native backend systems (AWS, Azure, or GCP)