About this role
Accountabilities:: Design, architect, and deliver end-to-end LLM-powered applications and agentic workflows using Python. Develop and implement Retrieval-Augmented Generation (RAG) pipelines using enterprise data, embeddings, and vector databases. Build sophisticated, multi-step AI agents capable of planning, executing tasks, using external tools, and maintaining contextual memory. Leverage modern AI development frameworks, including LangChain, LangGraph, and AutoGen, to orchestrate intelligent workflows. Integrate AI-powered applications with APIs, backend services, and cloud-based platforms. Establish and implement strategies for evaluating AI systems, ensuring accuracy, reliability, scalability, and performance. Monitor and optimize application performance, focusing on latency, operational costs, and overall solution efficiency. Take ownership of the complete development lifecycle, from technical architecture and development through deployment and continuous improvement. Requirements: 2–3 years of hands-on experience developing and implementing agentic AI workflows. Strong proficiency in Python, with demonstrated experience building and deploying production-grade backend applications. Practical experience developing LLM-powered applications, including prompt engineering, LLM orchestration, and integration. Proven expertise in RAG architectures, embeddings, semantic search, and vector database technologies. Hands-on experience with agentic AI frameworks such as LangChain, LangGraph, or AutoGen. Strong system design and software architecture skills, with experience developing and scaling cloud-based applications. Ability to integrate AI solutions with APIs, enterprise systems, and backend infrastructure. Understanding of AI evaluation methodologies and performance optimization, including accuracy, latency, and cost management. Strong analytical, problem-solving, and communication skills, with the ability to take ownership of complex technical projects. Experience in the healthcare insurance industry, particularly within the payer domain, is a strong advantage. Benefits: Compensation: $60 per hour. Work arrangement: 100% remote within the United States. Flexibility: Remote working opportunity, with flexibility for the right candidate. Career development: Opportunities to work with advanced AI technologies, LLM applications, and emerging agentic systems. Professional growth: Exposure to enterprise-scale AI projects and innovative technology solutions. Additional perks: Employee discounts and career flexibility and growth opportunities. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1
- LOCATION
- Remote · US, United States
- WORK MODE
- Remote
- JOB TYPE
- Full-time
- POSTED
- Nov 2, 2026
Source: Jobgether Careers