Forward Deployed Engineer

TekVivid, Inc; San Jose (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

TekVivid, Inc. is seeking an experienced Forward Deployed Engineer in Applied AI to lead the delivery of Conversational AI pilots at customer sites. You will transform rapid prototypes into production-ready agentic solutions and own end-to-end engineering lifecycle from concept to real-world business value.

You will architect flows linking Google’s AI products with customers’ live infrastructure, build scalable Eval pipelines, and travel to customer sites up to 50% to drive adoption and success.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, a related field.
• 5 years of experience with software development using Python or similar coding languages.
• Experience architecting AI systems on cloud platforms (e.g., GCP).
• 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.

Responsibilities

• Serve as the lead developer for complex Conversational AI and CX applications, transitioning prototypes to production-grade workflows.
• Architect and code conversational flows optimized for integration with customers’ live infrastructure and security perimeters.
• Build Eval pipelines and observability frameworks to optimize agent workloads with low latency and high security.
• Identify repeatable field patterns in Google’s AI stack and turn them into reusable modules or feature requests.
• Co-build with customer engineering teams to enforce best practices and ensure long-term project success.

Skills

Python

GCP

Terraform

Full-stack development

MLOps

API integration

Education

Bachelors in Engineering or CS

Masters/PhD in AI/CS

Tools

DialogFlow

ReAct framework

Job description

The key project experience and skill needed is conversational AI experience using Gemini customer experience (GECX)- CCAI, DialogFlow etc.

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.
• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 5 years of experience with software development using Python or similar coding languages.
• Experience architecting AI systems on cloud platforms (e.g., GCP).
• 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.
• Ability to travel up to 50% of the time.