Senior Forward Deployed Engineer - Lead Software Engineer

Capgemini Sogeti is hiring a Senior Forward Deployed Engineer to lead end-to-end engineering for applied AI initiatives in customer environments. This hybrid role focuses on turning conversational prototypes into production-grade, secure agentic workflows while establishing early Customer User Journeys (CUJs) on customer sites.

Key Responsibilities

• Act as the Agent Engineer for Applied AI, serving as the primary driver behind customers’ most critical AI initiatives.
• Own end-to-end engineering for conversational systems, from initial prototypes through production-ready, scalable, and secure AI workflows.
• Lead technical delivery for Conversational AI pilots and establish the first Customer User Journeys (CUJs) for major customers at their sites.
• Build high-performance evaluation (Eval) pipelines and observability frameworks to improve complex agentic workloads, with attention to reasoning loops, tool selection, and latency.
• Identify repeatable field patterns and technical friction points in the Google AAI stack, translating them into reusable modules or feature requests for Engineering teams.
• Co-build with customer engineering teams to apply Google-grade development best practices to support long-term delivery and adoption.
• Serve as the lead developer for complex Conversational AI and CX applications, moving from rapid prototypes to production-grade agentic workflows (including multi-agent systems and MCP servers) that support measurable ROI.
• Architect and implement conversational flows that connect Google Conversational AI products with customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
• Debug agent logic and optimize tool selection, including tracing conversation IDs across microservices to identify and resolve real-time failures.
• Connect agents to enterprise knowledge bases and optimize RAG chunking to reduce hallucinations.

Required Qualifications

• 10+ years of experience in software development using Python or similar coding languages.
• Experience leading complex Conversational AI and CX development, transitioning from prototypes to production-grade agentic workflows such as multi-agent systems and MCP servers.
• Experience architecting and coding conversational flows that integrate Conversational AI products with customer infrastructure, including APIs, legacy data silos, and security boundaries.
• Experience architecting AI systems on cloud platforms such as GCP.
• Experience deploying and automating agent, function, or networking setup using Terraform or similar tools.
• Experience building full-stack applications that interact with enterprise IT infrastructure and delivering external customer projects.
• Experience implementing multi-agent systems using frameworks such as ReAct and self-reflection.
• Experience debugging agent logic and optimizing tool selection, including conversation ID tracing across microservices for real-time failure resolution.
• Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to help prevent hallucinations.

Technical Skills and Tools

• Python
• Google AAI stack
• Machine Learning Operations
• GCP
• Terraform
• MCP servers
• Multi-agent systems
• ReAct
• Self-reflection
• RAG

Benefits

• Paid time off based on employee grade (A-F): Vacation: 12-25 days depending on grade; company paid holidays; personal days; sick leave.
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
• Retirement savings plans (401(k) in the U.S., RRSP in Canada).
• Life and disability insurance.
• Employee assistance programs.

Location and Work Model

This is a hybrid role based across multiple locations: Atlanta, Nashville, Chicago, Dallas, and New Jersey.

Compensation

The base compensation range for the posted location is USD 88,544 - 207,401 per year.

Additional Notes (U.S. and Canada)

Other benefits are provided based on local policy and eligibility.