Senior Forward Deployed Engineer - Lead Software Engineer

Capgemini offers a hybrid, customer-facing role where you help turn applied AI prototypes into production-ready, secure solutions. This is a high-impact Forward Deployed Engineer position focused on leading technical delivery at client sites, shaping early customer user journeys, and helping teams move from experimentation to measurable business outcomes.

What you’ll do

• Serve as the Forward Deployed Engineer (FDE) in Applied AI, acting as the Agent Engineer and primary driver for customer-critical conversational AI initiatives.
• Own the end-to-end engineering lifecycle, transforming conversational prototypes into production-ready systems that can scale securely.
• Lead Conversational AI pilots with an emphasis on first Customer User Journeys (CUJs) for major customers at their sites.
• Build evaluation (Eval) pipelines and observability frameworks for complex agentic workloads, including reasoning loops, tool selection, latency reduction, and production-grade security and networking.
• Surface repeatable field patterns and technical friction points in the Google AAI stack, then convert them into reusable modules or engineering feature requests.
• Collaborate with customer engineering teams to embed Google-grade development best practices to support long-term success and high end-user adoption.

What you bring

• 10+ years of software development experience using Python or similar coding languages.
• Experience serving 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 deliver measurable ROI.
• Ability to architect and code conversational flows optimized for the connective tissue between Google Conversational AI products and customer infrastructure, including APIs, legacy data silos, and security perimeters.
• Experience architecting AI systems on cloud platforms such as GCP.
• Experience deploying and automating agent resources using Terraform or similar tools.
• Experience building full-stack applications that integrate with enterprise IT infrastructures and supporting external customer projects.
• Experience implementing multi-agent systems using frameworks such as ReAct and self-reflection.
• Strength in debugging agent logic and optimizing tool selection, including tracing conversation IDs across microservices to resolve failures in real time.
• Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to help prevent hallucinations.

Technologies you’ll work with

• Python, Machine Learning Operations, cloud infrastructure
• Google AAI stack, GCP
• Terraform
• Multi-agent systems, MCP servers, ReAct
• RAG, microservices, APIs

Compensation

USD 88,544 - 207,401 per year.

Hybrid work location

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

Benefits

• Paid time off based on employee grade (A-F), defined by policy: 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 (for example, 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs