Full Stack Agentic AI Developer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Mindbank Consulting Group, is seeking the following. Apply via Dice today! Job Title: Full Stack Agentic AI Developer Location: Hybrid - Bethesda, MD 3 days onsite and 2 days remote Work Permit: or s work permit Pay: 130,000.00 - 140,000.00

: Medical, Dental, Vision, plus PTO, Holiday Pay, Paid Government Holidays and 10 paid vacation days, 401k w/match, Life Insurance and more. Work Hours: Monday - Friday - 40 hours per week

: Mindbank Consulting Group has an immediate need for a motivated and forward-thinking Full-Stack Agentic AI Developer to build autonomous, goal-driven AI integrated into existing production-ready applications/products for a large clinical trials system. The Full-Stack Agentic AI Developer will blend deep technical fluency in agentic frameworks with a product-centric mindset, designing, building, and orchestrating multi-agent systems that plan, reason, use tools, and recover from errors. This position is hybrid, working onsite in the Bethesda, Maryland office 3 days per week and 2 days per week from your home office. Full-Stack Agentic AI Developer

: Implement proof of concept through production-ready capabilities that directly improve clinical trial processes for a large system supporting cancer clinical trials. Design, build, and deploy autonomous AI agents capable of understanding high-level goals, planning actions, and executing tasks with minimal human intervention. Utilize frameworks like LangChain, LangGraph or CrewAI to build LLM-powered workflows. Build robust backend services (Python/REST API/Node.js) and Spring boot RESTful APIs to support agent orchestration and user interfaces. Create intuitive interfaces (React, Next.js, TypeScript) for users to monitor, configure, and intervene in AI agent workflows with human-in-the-loop. Develop custom tools, plugins, and Model Context Protocol (MCP) servers to securely expose internal services, APIs, and databases to LLMs. Architect and optimize Retrieval-Augmented Generation (RAG) pipelines and vector databases. Deploy AI applications on cloud platforms (AWS, Azure, or Google Cloud Platform) using Docker, Kubernetes, and CI/CD pipelines. • Implement observability, logging, tracing (e.g., LangSmith, Langfuse), and guardrails to monitor AI performance, cost, and safety. Full-Stack Agentic AI Developer