Resumen del puesto por JobGrid
Full Stack Agentic AI Developer - Local to Maryland at bounteous: Rockville, Estados Unidos; Presencial; Tecnología; Ingeniería Full Stack. This listing is part of JobGrid's Empleos de software engineer en páginas de empresas. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Rockville, Estados Unidos, Presencial
- Role classification: Tecnología, Ingeniería Full Stack
- Source freshness: checked by JobGrid on 2026-06-10.
- Application path: candidates continue to the employer application page with non-personal referral tags.
Role: Full-Stack Agentic AI Developer
Work model : Hybrid - 3 days from Bethesda, MD, USA office, 2 days WFH
Duration : June 2026 - Feb 2027 (Possible extension)
Job Description
Job Summary
Our client is seeking 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. You 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.
The role requires working 40 hours per week from June 2026 through February 2027.
This position is to work onsite at our office in Bethesda, Maryland office 3 day per week and 2 days per week from your home office.
Information Security Responsibilities
- Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols
- Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets
- Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.)
- Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information
Job Responsibilities
- • 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 GCP) using Docker, Kubernetes, and CI/CD pipelines.
- • Implement observability, logging, tracing (e.g., LangSmith, Langfuse), and guardrails to monitor AI performance, cost, and safety.
Basic Qualifications
- • Bachelor's degree in computer science or related field.
- • 3+ years of professional full-stack development experience with a focus on AI applications and data pipelines.
Preferred Qualifications
- • Strong proficiency in Python and JavaScript/TypeScript.
- • Familiarity with OpenAI API, LangChain or LangGraph and has hands on experience in developing AI agent workflows
- • Strong full-stack development with front-end experience in React.js; back-end expertise in Spring boot REST APIs, FastAPI, Flask, or Node.js; and database proficiency in Oracle, SQL (PostgreSQL) and NoSQL/Vector databases.
- • Experience with AWS Bedrock/Agents, Agentic AI workflows and CI/CD tools.
- • Exposure to Databricks, PySpark, Vector Search and MLFlow framework would is a plus
- • Familiarity with emerging AI tools like Claude Code, Codex or others and has experience in governing autonomous AI systems.