- 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 authority.
- Core Technical Stack: Absolute mastery of Java, Spring Boot, and Python for developing secure, high-throughput, cloud-native backend systems (AWS, Azure, or GCP).
- 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).
- AI 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 patterns.
- Systems Infrastructure & Data: Strong background in distributed systems, event-driven architectures, asynchronous processing, and messaging platforms (e.g., Kafka).
- Production Safeguards & MLOps: Proven experience implementing enterprise AI guardrails, including real-time observability, latency/cost monitoring, automated evaluation pipelines, and robust fallback mechanisms.
- Collaboration: Impact-driven mindset with excellent cross-functional communication skills to bridge Engineering, Product, Design, and Operations.
- Advanced Agentic AI: Experience building autonomous, multi-step agentic systems utilizing multi-tier memory networks and recursive reasoning preferred.
- Domain Expertise: Prior background in Healthcare IT, Revenue Cycle Management (RCM), billing, claims processing, fintech, or similarly regulated, high-compliance transaction environments preferred.
- Deep Data Retrieval: Hands-on experience with vector databases, semantic search architectures, and enterprise knowledge graph construction preferred.
- Advanced ML Tooling: Exposure to PyTorch, Hugging Face Transformers, custom embedding models, fine-tuning methodologies, or model serving optimization.
- Leadership Pedigree: Past experience serving as a Founding Engineer, Principal Architect, or early-stage platform lead driving organization-wide AI/ML adoption frameworks preferred.
(For Recruiter use only) #LI-SS1 #LI-Remote
We are dedicated to attracting and retaining top talent with competitive and fair compensation. For this position, this range reflects our Zone 1 (National Average) pay band. Your specific compensation is thoughtfully determined by your experience, qualifications, the specific requirements of the role, and your Geo Zone. Our geo-zone system ensures your pay is competitive for your location, recognizing varying costs of labor across regions.
Our four geo zones are designed to reflect this: Zone 1: National Average Zone 2: Moderately Higher Cost Regions Zone 3: High-Cost Regions Zone 4: Lower-Cost Regions
Beyond base compensation, Tebra offers eligible employees the opportunity for variable pay and a robust benefits package, reflecting our commitment to your overall well-being. In compliance with California pay transparency laws, the specific compensation range applicable to your Geo Zone will be shared during your initial talent screen.