Provide Thought leadership in the future opportunities in AI and agentic-enabled tools, capabilities, and challenges
Serve as the architectural lead for AI- and agentic-enabled tooling, establishing patterns, reference implementations, and best practices.
Design scalable, secure, and resilient software systems that integrate LLMs, multi-agent workflows, code intelligence, and automation.
Own and drive the technical roadmap for next-generation software acceleration tools—including IDE extensions, code-analysis agents, refactoring engines, and developer-assistive AI.
Lead architecture reviews, evaluate new technologies, and set engineering standards for AI safety, quality, reliability, and observability.
Build high-quality software with modern languages and frameworks (e.g., Python, TypeScript, Go, Java).
Develop pipelines and services that enable AI reasoning, code analysis, static/dynamic analysis, and automated transformation of legacy systems.
Prototype early concepts rapidly and transition successful prototypes into robust, production systems.
Integrate AI/ML models (commercial, open-source, or custom) into enterprise environments and developer workflows.
Design and build agentic orchestration, tool-use interfaces, embeddings systems, context windows, and retrieval-augmented workflows.
Implement “human-in-the-loop” safety and review patterns.
Develop mechanisms for grounding, guardrailing, and evaluating AI performance and correctness.
Leverage AI to analyze, modernize, and refactor large, complex codebases (e.g., Java, .NET, COBOL, C++).
Partner with product, UX, and platform teams to define features, user journeys, and developer experience goals.
Act as a technical mentor to senior and mid-level engineers; cultivate a culture of excellence and continuous learning.
Collaborate closely with research, data, and cybersecurity teams to ensure solutions are safe, secure, and aligned with mission needs.
Represent the engineering team in internal and external forums, contributing to thought leadership in AI and software engineering modernization.

Requirements

15+ years experience in software engineering
Expertise in designing and building distributed systems, developer tools, or platform engineering products
Hands-on experience implementing AI/ML systems or integrating large language models into production workflows
Strong knowledge of agentic frameworks, orchestration tools, RAG, vector databases, API design, and microservices
Deep understanding of software design patterns, CI/CD, DevSecOps, and cloud-native architectures (AWS/Azure/GCP)
Strong coding proficiency in at least two modern languages (Python, Go, Java, C#, etc.)
Ability to drive technical strategy, influence cross-functional teams, and communicate complex ideas clearly
Must be authorized to work in the U.S.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonTypeScriptGoJavaC#AI/ML systemslarge language modelsdistributed systemssoftware design patternsCI/CD

Soft Skills

thought leadershiptechnical mentorshipcommunicationinfluence cross-functional teamsdrive technical strategycollaborationcultivate culture of excellencecontinuous learning