Data Architect

Role Summary

As a Forward Deployed Engineer in Applied AI, you will serve as an Agent Engineer and drive critical AI initiatives. You will transform initial conversational prototypes into production-ready solutions while owning the end-to-end engineering lifecycle and delivering scalable, secure AI systems that create measurable business value.

This role focuses on leading technical delivery for Conversational AI pilots and establishing initial Customer User Journeys. It 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 customer-experience applications.
• Transition rapid prototypes into production-grade agentic workflows, including multi-agent systems and MCP servers.
• Architect and code conversational flows optimized for integration between Conversational AI products and live infrastructure.
• Integrate solutions with APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation pipelines and observability frameworks for complex agentic workloads.
• Optimize reasoning loops, tool selection, and latency while maintaining production-grade security and networking.
• Identify repeatable field patterns and technical friction points in the Applied AI stack.
• Convert recurring patterns into reusable modules or product-feature requests for engineering teams.
• Co-build with customer engineering teams and establish strong development practices.
• Support 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.
• Five years of software-development experience using Python or a similar programming language.
• Experience architecting AI systems on cloud platforms such as GCP.
• Experience deploying resources through Terraform or similar tools to automate the setup of agents, functions, or networking.
• Experience building full-stack applications that interact with enterprise IT infrastructure.
• Experience developing external customer projects.

Preferred Qualifications

• Master's degree or Ph.D. in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using patterns such as ReAct and self-reflection.
• Experience debugging agent logic and optimizing tool selection.
• Experience tracing conversation identifiers across microservices to diagnose and resolve real-time failures.
• Experience connecting agents to enterprise knowledge bases.
• Experience optimizing RAG chunking to prevent hallucinations.
• Track record of troubleshooting live, high-traffic systems during critical windows.
• Ability to travel up to 50 percent of the time.