Applied AI Engineer

• Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Own the delivery of the Customer User Journeys (CUJs), ensuring that conversational flows are not just functional, but optimized and production ready for [top customer/industry priorities].
• Architect and optimize complex agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
• Implement critical infrastructure including rate limiting, error managing, and regional failover strategies; develop monitor systems and alerting dashboards during "Go-Live" windows to ensure stability as traffic scales.
• Travel up to 50% of the time.

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 6 years of experience with software development using Python or similar coding languages.
• Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
• Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems.
• Experience developing and deploying multilingual natural language processing models.

Preferred qualifications:

• Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
• Experience in debugging Agent logic (ReAct loops, Chain of Thought) and optimizing tool selection.
• Experience with troubleshooting live, high-traffic systems during critical windows.
• Ability to trace conversation IDs across microservices to identify and resolve failures in real-time.

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 6 years of experience with software development using Python or similar coding languages.
• Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
• Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or RAG systems.
• Experience developing and deploying multilingual natural language processing models.