Agentic AI Engineer

About the Role

We are evolving our chat experience from human-assisted to fully agentic. As an AI Agentic Software Engineer, you will help rewrite an existing production application into an end-to-end agentic platform, with a strong passion for customer experience and a commitment to building intuitive, high-quality interactions.

This role is for engineers who treat AI as a core part of the system—embedded across the full SDLC to deliver production‑grade outcomes—while continuously advocating for the end user. You’ll work in a Google‑centric stack using tools like ADK and Gemini Enterprise to build complex, agent-driven experiences that are not only intelligent, but seamless, trustworthy, and delightful for customers.

• Agentic & AI-Augmented Engineering
• Design, build, and operate agentic systems that replace or augment human workflows
• Apply AI across the SDLC, including:
• Requirements and spec‑driven development
• System and agentic workflow design
• AI‑augmented coding and refactoring
• AI‑driven testing and defect remediation
• Treat AI as a collaborating system, not a one‑off tool
• Evaluate and iterate on AI outputs (e.g., LLM‑as‑a‑Judge)
• Platform & Production Delivery
• Build production‑ready agent‑based solutions with reliability, scalability, and observability
• Implement agent‑to‑agent, agent‑to‑UI, and human‑AI orchestration
• Contribute to Agent Ops, MLOps, and AI governance
• Ensure ethical, compliant, and responsible AI use.
• Collaboration & Influence
• Clearly communicate how AI is used in your engineering workflows
• Share patterns and best practices with the team
• Partner with product, UX, and platform teams to deliver cohesive experiences.

• 2+ years building agentic AI systems in production, or equivalent experience designing, shipping, and operating scalable, production‑grade software (APIs, platforms, workflow engines, or customer‑facing applications)
• Hands‑on experience with Agent Development Kit (ADK) and Python
• Experience with Gemini Enterprise, or similar conversational AI platforms
• Spec‑driven development with AI integrated into the development lifecycle
• Strong prompt engineering skills, including evaluation, iteration, and logging
• Experience leveraging AI‑assisted coding across multiple features or defects in parallel
• Familiarity with Agent Ops and production monitoring for agent‑based systems
• Experience with LLM‑as‑a‑Judge or comparable evaluation techniques
• Proven ability to design agent‑to‑agent, agent‑to‑UI, and human‑AI collaboration patterns
• Soft Skills:
  
  Curiosity to explore emerging AI capabilities, critical thinking to assess AI outputs, and adaptability in fast‑moving, ambiguous environments.

Disclaimer:
This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.