Why This Role Stands Out
This role offers significant opportunities to drive impactful projects within Applied AI, perfect for ambitious mid-senior engineers eager to deepen their expertise. You will thrive here if you enjoy hands-on problem-solving and are passionate about leveraging cutting-edge technology to create innovative solutions. Apply now to join a dynamic team and shape the future of AI.
Quick Overview
Job Description
Role: Forward Deployed Engineer
Locations: Mountain View, CA (Fully Onsite)
Duration: 12+ Months Contract
F2F Interview MUST For Local Candidates
Note: Candidate needs to be in the office 5 Days every week. Local or candidates from adjacent states only.
Ability to travel up to 50% of the time.
GECX certification is mandatory
Job Description:
- As a Forward Deployed Engineer (FDE) in Applied AI, you are the "Agent Engineer" and the primary driver for our customers' most critical AI initiatives.
- You take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering lifecycle, including the transition from "Art of the Possible" to real-world business value and scalable, secure AI systems. This is a high-travel, high-impact role focused on leading technical delivery for Conversational AI pilots and establishing the first Customer User Journeys (CUJs) for our largest customers at their sites.
- This role requires a deep understanding of software engineering, Machine Learning Operations, and cloud infrastructure.
Job responsibilities:
- Serve as the lead developer for complex Conversational AI and CX applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" between Google s Conversational AI products and customers live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build high-performance evaluation (Eval) pipelines and observability frameworks to optimize complex agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
- Identify repeatable field patterns and technical "friction points" in Google s AAI stack, converting them into reusable modules or product feature requests for Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
Minimum Qualifications:
- Bachelor s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience with software development using Python or similar coding languages.
- Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
- Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
- Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
Preferred qualifications:
- Master s or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
- Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
- Track record of troubleshooting live, high-traffic systems during critical windows.
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