Job description: EDUCATION, EXPERIENCE, & SKILLS REQUIRED 8–11 years of experience in a software engineering role, with a focus on backend or full-stack development Proven track record of AI/LLM application development or integration Strong experience in Python-based AI application development with API engineering Proficiency in RESTful APIs, microservices, and cloud-based AI deployments (AWS, Kubernetes, Lambda) Familiarity with AI orchestration tools for AI workflow automation Knowledge of SQL and NoSQL databases (PostgreSQL) for AI-powered search Experience working in Agile teams and delivering AI-driven features in a cloud-first environment Bachelor’s Degree in Computer Science or related field Understanding of healthcare data privacy regulations (HIPAA, GDPR) is a plus BEHAVIORS & ABILITIES REQUIRED Ability to learn and adapt rapidly while producing high-quality code Capable of translating AI/LLM concepts into practical, scalable software solutions Innovative thinker who finds creative ways to execute when historical context is limited Strong analytical skills to assess potential designs and choose the best solution for the business Committed to delivering results under challenging circumstances Skilled at mentoring and coaching to elevate junior team members Able to uphold best engineering practices for quality, security, and performance RESPONSIBILITIES MAY INCLUDE, BUT ARE NOT LIMITED TO Technical Execution AI-Powered Software Development & API Integration Design, develop, and deploy AI-powered applications that enhance RCM automation Develop AI-driven microservices and ensure cloud-native deployment. AI Optimization & Performance Tuning Optimize AI model performance via API configurations rather than custom fine-tuning Leverage AI orchestration tools (LangChain) to automate complex AI workflows Microservices & APIs Build and maintain RESTful APIs for AI features; integrate with internal and external systems Accurately estimate development tasks and own them through completion Deliver high-quality software components Ensure solutions meet reliability, performance, and compliance standards (especially for healthcare data) Evaluate and propose new technologies Identify scalable open-source frameworks or cloud-based AI services, ensuring robust and cost-effective implementations Code reviews & quality assurance Participate in peer reviews, ensuring adherence to coding conventions and best practices Write, debug, and deploy code to production, promptly delivering fixes Contributions to the Team Subject matter expert Serve as a go-to resource for AI/LLM-related application architecture and best practices Stay current with industry trends (agentic AI, genAI) and share insights with the broader team Scrum team participation Collaborate in Agile ceremonies: daily stand-ups, sprint planning, retrospectives Commit to sprint goals and deliver incremental value to customers and internal stakeholders Team accountability Encourage a culture of ownership: if you build it, you support it post-release Help the team continuously improve velocity, code quality, and automation Cross-Functional Coordination & Communication Partner with product and UX Translate requirements for AI-driven RCM features into technical designs, ensuring alignment with user needs Collaborate on user experience improvements requiring generative AI insights (e.g., claims code suggestions) Stakeholder engagement Work closely with compliance/security teams to maintain HIPAA/data governance standards Communicate technical roadmaps, dependencies, and timelines effectively to non-technical audiences Broad knowledge sharing Educate peers on AI/ML design patterns, cloud infrastructures, and best practices Build strong relationships with cross-functional teams, bridging technology and business domains Show more Show less