Full Stack Software Engineer 3

Full Stack Software Engineer - Post Billing Processing System

Position Overview
We are seeking a highly skilled and motivated Full Stack Engineer to join our team responsible for developing and maintaining a robust Post Billing Processing system within the healthcare insurance domain. The ideal candidate will have a strong background in full-stack software development, including front-end and back-end technologies, database management, and cloud platforms. Experience with workflow automation and an interest in applying AI/LLM technologies to enhance system capabilities are also valuable. This role involves designing, building, and optimizing the end-to-end system for appealing denied insurance claims.

Responsibilities

• Design, develop, test, deploy, and maintain the full stack of the Post Billing Processing system, including front-end interfaces, back-end services, databases, and infrastructure components (e.g., Denial Code Manager, Workflow Orchestrator, Template Generation Engine, Outbound Package Preparation, Automated Outbound Communication).
• Collaborate with business stakeholders, product managers, and other engineers to understand requirements and translate them into technical specifications and robust, scalable software solutions.
• Develop and manage APIs for internal and external system integrations.
• Implement and manage database schemas and optimize queries for performance.
• Work with cloud services (AWS) for deployment, monitoring, and scaling.
• Contribute to the implementation and optimization of automated workflows (e.g., using AWS Step Functions).
• Participate in code reviews, testing (unit, integration, end-to-end), and optimization efforts.
• Create and maintain comprehensive documentation for system architecture, components, APIs, and processes.
• Ensure system security, data privacy, and compliance with healthcare regulations (e.g., HIPAA).
• Provide ongoing support and maintenance, troubleshooting and resolving issues promptly.
• Stay updated with the latest advancements in full-stack development technologies and best practices.

Required Skills and Qualifications

• Technical Skills
• Strong proficiency in programming languages such as Python and/or Node.js.
• Experience with front-end technologies (e.g., React, Angular, Vue.js, HTML, CSS, JavaScript).
• Experience with back-end frameworks (e.g., Express, Django, Flask).
• Experience with relational databases (e.g., PostgreSQL, MySQL) and/or NoSQL databases (e.g., MongoDB, DynamoDB).
• Experience designing and consuming RESTful APIs.
• Experience with cloud platforms (AWS preferred) and core services (e.g., EC2, S3, RDS, Lambda).
• Experience with containerization technologies (Docker, Kubernetes).
• Experience with version control systems (Git).
• Understanding of software development lifecycle (SDLC) and agile methodologies.
• Strong analytical and problem-solving skills.
• Soft Skills
• Excellent communication and collaboration skills.
• Ability to work effectively in a team environment.
• Strong organizational and time management abilities.
• Attention to detail and commitment to delivering high-quality, reliable software.
• Ability to work in a fast-paced, dynamic environment.

Education

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Experience

• Proven experience working as a Full Stack Engineer, developing and deploying web applications.
• Experience with workflow automation tools (e.g., AWS Step Functions).
• Experience working within the healthcare or insurance domain is a plus.

Bonus Skills / Experience (Highly Desirable)

• Hands-on experience with LLMs (e.g., OpenAI APIs, Llama2, Mistral) and integrating them into applications.
• Familiarity with AI/ML frameworks like LangChain, LangGraph, or Haystack.
• Experience building RAG (Retrieval-Augmented Generation) solutions.
• Knowledge of Vector Databases (e.g., Pinecone, Milvus) or Graph Databases (e.g., Neo4j).
• Understanding of prompt engineering techniques.
• Experience with advanced RAG techniques (e.g., HyDE, LLM reranking).
• Experience creating embeddings (e.g., using Ada models).