Forward Deployed Engineer – Conversational AI / GCP

In4ge is a recruitment company focused on connecting talented professionals with appropriate companies to foster growth and success. They believe true value is created by people working together in an atmosphere of mutual respect and trust.

• Higher education degree in engineering, computer science, or a related field, or equivalent practical experience.
• Minimum 5 years of software development experience in Python or similar programming languages.
• Experience in designing AI system architectures on cloud platforms such as GCP.
• Experience deploying resources using Terraform or similar tools, automating configuration of agents, functions, or networks.
• Experience developing full stack applications integrated with corporate IT infrastructure.
• Experience delivering projects for external clients.
• Good understanding of software engineering, MLOps, and cloud infrastructure.
• Willingness to travel up to 50% of the time.

Nice to have:

• Master's or doctoral degree in AI, computer science, or a related technical field.
• Experience implementing multi-agent systems using approaches like ReAct and self-reflection.
• Experience debugging agent logic and optimizing tool selection, including tracking conversation IDs across microservices to detect and resolve real-time errors.
• Experience integrating agents with corporate knowledge bases and optimizing document chunking in RAG solutions to reduce hallucinations.
• Experience troubleshooting high-traffic, production-critical systems under critical operating conditions.

• Acting as the lead developer in complex Conversational AI projects and customer experience applications.
• Transforming prototypes into production agent solutions, including multi-agent systems and MCP server-based solutions delivering measurable business value.
• Designing and programming conversational flows and integrating them with customer's existing infrastructure including APIs, legacy data systems, and security mechanisms.
• Building efficient evaluation pipelines and monitoring and analysis mechanisms for agent performance.
• Optimizing agent reasoning loops, tool selection, and latency while meeting security and network requirements in production environments.
• Identifying recurring deployment scenarios and technical issues, transforming them into reusable modules or product development proposals.
• Collaboratively creating solutions with client engineering teams and implementing good software development practices.
• Supporting long-term project success and effective use of the solution by end users.
• Technically leading pilot deployments and creating initial user paths at client sites.