Principal Software Architect (GenAI Applications and Agentic Systems)

OpenText Corporation•Gaithersburg, MD

53d•Hybrid

About The Position

OpenText is a global leader in information management, where innovation, creativity, and collaboration are the key components of our corporate culture. As a member of our team, you will have the opportunity to partner with the most highly regarded companies in the world, tackle complex issues, and contribute to projects that shape the future of digital transformation. AI-First. Future-Driven. Human-Centered. At OpenText, AI is at the heart of everything we do-powering innovation, transforming work, and empowering digital knowledge workers. We're hiring talent that AI can't replace to help us shape the future of information management. Join us. Principal Software Architect (GenAI Applications and Agentic Systems) in Gaithersburg, MD, USA (Hybrid) OpenText's AI Engineering and Enablement team is building the foundational components and developer experiences that power intelligent applications across our product portfolio. Your Impact: As a Principal Software Architect (GenAI Applications and Agentic Systems), you will serve as a senior engineer responsible for designing, building, and extending the agentic runtimes, orchestration flows, and shared GenAI services that form the backbone of our AI platform strategy. You will lead the implementation of reusable GenAI components such as agent frameworks, RAG pipelines, vector-augmented retrieval services, and semantic memory. You will work in close partnership with architects and fellow engineers to productionalize fast-moving incubation efforts, extend orchestration frameworks, and enable scalable agentic solutions that can be reused across products and deployment environments. This is a hands-on role for an experienced AI systems engineer who can take ownership of complex capabilities, deliver robust implementations, and contribute directly to the enablement of AI-powered applications across OpenText.

Requirements

Writing clean, modular Python code using FastAPI, with a strong understanding of system integration and runtime performance.
Applying and adapting frameworks such as LangChain, LangGraph, CrewAI, or other orchestration platforms to enterprise use cases.
Designing agent workflows that incorporate tools, memory, vector search, structured reasoning, and secure execution.
Understanding and implementing A2A interaction flows and integrating agents with tools and resources using MCP.
Building scalable RAG systems, and optimizing embedding usage, query strategies, and semantic relevance scoring.
Working across the full development lifecycle from prototype to hardened implementation, with strong test and monitoring practices.
Collaborating with teams working in Java and TypeScript environments, contributing to cross-language integration and API design.
Mentoring developers and reviewing pull requests to uphold engineering standards across agentic codebases.
10+ years of software development experience, including 2-4 years focused on GenAI or agentic AI development.
Strong proficiency in Python, with real-world experience using FastAPI to build service-oriented systems.
Direct experience implementing agent flows using LangChain, LangGraph, CrewAI, or similar frameworks.
Experience implementing RAG pipelines, working with vector databases, embedding models, and hybrid retrieval strategies.
Working knowledge of MCP and A2A patterns, with hands-on experience integrating agents, tools, and services into orchestrated flows.
Ability to work with and around Java and TypeScript-based applications, including REST and event-driven interfaces.
Demonstrated ability to ship complex systems in collaboration with architects, product managers, and infrastructure teams.
Strong documentation and communication skills to support reusability and onboarding

Nice To Haves

Familiarity with knowledge graphs and structured reasoning models is a strong plus.

Responsibilities

Designing and developing production-ready components for GenAI applications, including agent workflows, tool execution layers, vector search integrations, and memory modules.
Implementing and optimizing retrieval-augmented generation (RAG) pipelines, including embeddings, hybrid retrieval, and contextual grounding.
Building reusable agent runtimes and orchestration logic, using frameworks like LangChain, LangGraph, CrewAI, or equivalent.
Participating in the development of multi-agent patterns, including asynchronous workflows and Agent-to-Agent (A2A) coordination.
Contributing to the integration of the Model Context Protocol (MCP) for standardized agent-to-tool and resource interactions.
Extending and integrating semantic reasoning into agent flows using knowledge graphs or other structured sources.
Collaborating with architects and cross-functional teams to translate high-level designs into modular, maintainable code.
Supporting internal enablement by delivering reference implementations, engineering documentation, and code-level onboarding materials.

Benefits

At OpenText, we offer a thoughtfully designed benefits package that supports your physical, emotional, and financial wellbeing.
As you move through the hiring process, we're happy to provide more details about our compensation programs, including variable and commission compensation opportunities for eligible roles, vacation entitlement, and paid time off.

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