Principal Software Engineer

As a Principal Engineer – Emerging Technology, you will be responsible for leading the analysis, design, and development of enterprise‑grade conversational AI solutions and adjacent applications to support critical business needs. You will work closely with Architects, Systems Developers, Project Managers, Scrum Masters, Quality Assurance Analysts, Product Owners, Product Managers, and Business Analysts to develop and maintain systems as designed. You will promote continuous learning with the development team to improve skills and practice.

The Principal Engineer is expected to perform design activities with an enterprise mindset. This involves understanding the complex interplay between mission‑critical applications, and the underlying architecture of applications themselves, along with the long‑term objectives of the business to ensure technology solutions best fit the long‑term vision of the organization. The Principal Engineer is the thought leader for the development team, understanding the architecture of the larger ecosystem and translating that to sound, forward‑looking design decisions for all applicable applications and team members.

• Define vision, roadmap, and architecture for enterprise‑scale conversational AI using Google Dialogflow CX and related AI/ML capabilities.
• Establish standards for chatbot architecture, API patterns, performance, scalability, reliability, and observability; participate in platform/software selection.
• Create reusable architectural patterns, accelerators, and best practices.

• Lead end‑to‑end design and implementation of virtual agents: flows, pages, intents, entities, parameters, state handlers, and fulfillment.
• Deliver experiences for both chat and telephony (call deflection, real‑time support).
• Own code quality (design reviews, code reviews), documentation, CI/CD, automated testing, and Level‑3 support.

• Lead the design and integrations with back‑end services via REST APIs and webhooks using Cloud Functions or Python/Node services.
• Lead and collaborate with API development teams to design and develop APIs and with API gateway teams (e.g., Apigee).

• Leverage Vertex AI, RAG, prompt engineering, agentic workflows to enhance guided experiences.
• Define evaluation strategies and governance for GenAI in Higher Education contexts.

• Implement automated testing (NLU evaluation, regression, E2E), monitoring, alerting, and SRE practices.
• Analyze conversation logs and NLU metrics to drive continuous optimization and ensure high‑availability, scalability, and resilience.

• Lead and mentor onshore/offshore engineers; coach on best practices and modern techniques.
• Lead PoCs, demos, and workshops. Propose new techniques and technologies for software development.

• Ensure adherence to security, privacy, data governance, and compliance policies; define controls for conversational data handling and auditing.

• Conversational AI:
  Deep expertise in Dialogflow CX (design, build, test, deploy; voice & chat) including flow design, fulfillment, and agent configuration.
• Programming:
  Proficiency in Python and/or Node.js; experience with Java/C# a plus.
• Cloud:
  Strong knowledge of GCP (Cloud Functions, IAM, Cloud Logging/Monitoring; Big Query desirable).
• Architecture & APIs:
  Microservices, REST API design, webhooks, eventing, scalability; API gateways (e.g., Apigee).
• AI/ML & GenAI: LLMs, RAG, prompt engineering, Vertex AI; evaluation and safety guardrails.
• Web & Databases: HTML/JS fundamentals; cross-browser compatibility; database design and SQL with Oracle and other RDBMS (e.g., Postgre
  
  SQL, MySQL).
• Engineering: CI/CD, automated testing, observability, performance tuning, reliability engineering.
• Soft Skills:
  
  Excellent communication, leadership, mentoring, and cross‑functional collaboration; proactive problem solving.

• 7+ years software development, systems implementation, and integrations.
• 5+ years with cloud technologies/infrastructure (GCP strongly preferred).
• 5+…