Principal Developer, Agentic AI

Overview:
About JAGGAER 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 1,200. 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
We are seeking a highly motivated Principal Engineer, Agentic AI to lead the design and technical direction of enterprise-scale, AI-powered applications, with deep expertise across backend and frontend development and a strong foundation in Artificial Intelligence (AI) and Generative AI technologies.
The ideal candidate will architect and drive the technical strategy for scalable enterprise applications, set engineering best practices, mentor senior and staff engineers, and lead the evolution of next-generation intelligent procurement experiences leveraging Large Language Models (LLMs), Agentic AI frameworks, and modern cloud technologies. Location: Hyderabad, India (In-Office)Employment Type: Full-TimeLevel: PrincipalReports To: VP of Architecture . Innovation, under the Chief Data . AI Officer (CDAO)Department: Data . AI Office

Principal Responsibilities:

• Agentic AI Architecture . Strategy:

• Own the end-to-end technical architecture and strategy for JAGGAER's Agentic AI platform, from agent design patterns to production deployment.

• Define the technical roadmap for autonomous and multi-agent systems, aligning architecture decisions with product and business strategy.

• Set architecture standards for agent orchestration, tool/function calling, and inter-agent communication across the platform.

• Define and govern integration standards, including MCP (Model Context Protocol) and RESTful APIs, for connecting agents to internal and external enterprise systems.

• Architect scalable vector search and retrieval infrastructure to support Retrieval-Augmented Generation (RAG) across the platform.

• AI . Agentic Systems:

• Architect and champion AI-powered applications leveraging Large Language Models (LLMs) and Generative AI technologies across the platform.

• Define the technical strategy for intelligent workflows using Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies.

• Design and guide the implementation of Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.

• Set best practices for prompt design, structured outputs, tool/function calling workflows, and AI orchestration pipelines.

• Lead the development of AI copilots, research assistants, recommendation engines, chatbots, workflow automation, and NLP-driven capabilities.

• Drive the design of multi-agent systems, agent orchestration, and autonomous workflow execution across the organization.

• Platform Integration . Analytics:

• Partner with upstream and downstream application teams and stakeholders to embed agentic AI capabilities across the platform's architecture, integration patterns, and data flow.

• Lead the integration of agentic AI and LLM-powered capabilities into the JAGGAER Analytics platform and related reporting experiences.

• Define the technical strategy for surfacing AI-generated insights through the Tableau Reporting Platform and other reporting services.

• Engineering Excellence . Leadership:

• Establish observability, evaluation, and performance monitoring standards to continuously improve AI system quality.

• Champion AI system performance, scalability, reliability, and security as core architectural tenets, including guardrails for safe and responsible agent behavior.

• Elevate engineering standards through rigorous architecture reviews, testing practices, and mentorship of engineers at all levels.

• Serve as a key technical voice across globally distributed Product Management, Engineering, Professional Services, and Customer Success teams, influencing roadmap and strategy.

Position Requirements:

• 10. years of experience in software development with deep expertise in Java and/or Python, including significant experience in technical leadership or architect roles.

• Proven track record architecting and delivering enterprise applications using Spring Boot, REST APIs, and Microservices architecture at scale.

• Strong experience building and guiding frontend applications using React.js and modern JavaScript frameworks.

• Deep understanding of software engineering principles, object-oriented design, data structures, algorithms, and enterprise architecture patterns.

• Extensive experience with Oracle and PostgreSQL databases, including advanced SQL, schema design, and performance optimization at scale.

• Demonstrated expertise in API integrations, enterprise system connectivity, and distributed application architectures.

• Hands-on experience with Generative AI concepts and a track record of integrating LLM-powered capabilities into production applications.

• Strong working knowledge of Agentic AI concepts, AI orchestration, prompt engineering, tool calling, and structured outputs.

• Demonstrated ability to mentor engineers, lead technical initiatives, and influence architectural decisions across teams.

• Excellent problem-solving, analytical, and debugging skills, with sound judgment on technical trade-offs.

• Ability to communicate clearly and persuasively in English, both verbally and in writing, including to technical and non-technical stakeholders.

Bachelor’s degree in Computer Science, Engineering, or equivalent; advanced degree a plus. *Nice-to-Haves:
+ Experience with LangChain, LangGraph, CrewAI, AutoGen, or similar Agentic AI frameworks.
+ Experience building AI-powered applications using Large Language Models (LLMs).
+ Experience implementing Retrieval-Augmented Generation (RAG) systems.
+ Familiarity with vector databases such as Pinecone, ChromaDB, Weaviate, or similar technologies.
+ Knowledge of multi-agent systems, workflow automation, and AI evaluation techniques.
+ Experience with MCP (Model Context Protocol) integrations.
+ Experience building AI copilots, autonomous agents, deep research assistants, chatbots, workflow automation systems, or AI-powered SaaS products.
+ Familiarity with AI observability, monitoring, and evaluation platforms.
+ Knowledge of AWS cloud services, DevOps practices, CI/CD pipelines, Docker, and Kubernetes.
+ Experience working with Snowflake and modern data platforms.
+ Knowledge of SonarQube and application quality management practices.
+ Familiarity with Data Source Manager (DSM) concepts, configuration, and integration within analytics and reporting ecosystems.
+ Exposure to procurement, analytics, reporting, business intelligence, or enterprise SaaS platforms.
+ Experience leading architecture reviews, technical design documents (RFCs), or engineering guilds.
+ Contributions to open-source projects, technical publications, or conference presentations in AI/ML or software engineering.



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