Senior Full Stack Developer, Agentic AI Research & Prototyping (US Remote) at Jaggaer
Durham, NC 27709, USA -
Full Time


Start Date

Immediate

Expiry Date

07 Sep, 25

Salary

0.0

Posted On

08 Jun, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Java, Security, Cassandra, Collaborative Environment, Vue, Mysql, Computer Science, Postgresql, Emerging Technologies, Mongodb, Maintainability, Angular, Redis, Testing

Industry

Information Technology/IT

Description

Overview:
JAGGAER provides an intelligent Source-to-Pay and Supplier Collaboration Platform that empowers organizations to manage and automate complex processes while enabling a highly resilient, responsible, and integrated supplier base. With 30 years of expertise, we specialize in solving complex procurement and supply chain challenges across various industries.
Our 1,300+ global employees are obsessed with ensuring customers get full value from our products - ultimately enhancing and transforming their businesses. For more information, visit www.jaggaer.com
JAGGAER is investing in next-generation AI and Agentic AI to revolutionize enterprise procurement. We’re seeking a Senior Full Stack Developer who thrives in early-stage product exploration and hands-on AI research and prototyping.
In this role, you’ll work on rapid experimentation—translating ideas into working demos using LLMs, orchestration frameworks like LangGraph or CrewAI, and robust Java-based backends with scalable data architectures. You’ll collaborate across AI, product, and architecture teams to inform the future platform roadmap.
Principal Responsibilities:

Position Responsibilities:

  • Rapidly prototype AI-driven use cases using Java-based services, frontend components, and integration of AI/ML tools.
  • Build POCs leveraging agentic AI frameworks (LangGraph, AutoGen, CrewAI) and test novel interactions with LLMs and external APIs.
  • Work with SQL/NoSQL databases to model knowledge graphs, embeddings, and AI-generated outputs at scale.
  • Develop intuitive UIs using React or Angular to test agent-based user workflows.
  • Partner with architects and ML engineers to evaluate AI frameworks and identify production candidates.
  • Translate architectural patterns into real-world test cases that help validate platform assumptions.

Position Requirements:

Position Requirements:

  • 12+ years of full-stack development experience.
  • Deep expertise in Java (Spring Boot, Micronaut, or Quarkus) for building scalable services and APIs.
  • Strong experience in database design and performance optimization (PostgreSQL, MySQL, MongoDB, Redis, or Cassandra).
  • Frontend proficiency in React, Angular, or Vue with UX sensitivity.
  • Cloud-native development experience (AWS/Azure/GCP).
  • Hands-on exposure to LLMs, vector search, and embedding frameworks (e.g., Pinecone, Weaviate).
  • Experience with orchestration frameworks like LangGraph, AutoGen, LangChain, or CrewAI.
  • High standards for performance, testing, security, and maintainability.
  • Degree in Computer Science or related field from a top-tier institution; Master’s a plus.
  • Passion for AI, emerging technologies, and agile prototyping in a collaborative environment.

Why JAGGAER?:

  • Work directly with the CDAO’s innovation team to shape the future of enterprise AI.
  • Influence platform direction from early-stage R&D.
  • Collaborate with world-class talent in a fast-paced, impact-driven culture.
  • Enjoy flexibility, purpose-driven work, and competitive compensation.
Responsibilities
  • Rapidly prototype AI-driven use cases using Java-based services, frontend components, and integration of AI/ML tools.
  • Build POCs leveraging agentic AI frameworks (LangGraph, AutoGen, CrewAI) and test novel interactions with LLMs and external APIs.
  • Work with SQL/NoSQL databases to model knowledge graphs, embeddings, and AI-generated outputs at scale.
  • Develop intuitive UIs using React or Angular to test agent-based user workflows.
  • Partner with architects and ML engineers to evaluate AI frameworks and identify production candidates.
  • Translate architectural patterns into real-world test cases that help validate platform assumptions
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