Capgemini is seeking a Senior Forward Deployed Engineer (Agent Engineer) to lead customer-critical conversational AI work from early prototypes to production-grade solutions. This hybrid role is based across multiple locations including Atlanta, Nashville, Chicago, Dallas, and New Jersey and is designed for engineers who enjoy hands-on technical delivery at customer sites, with a high-impact, travel-enabled focus on establishing first customer user journeys (CUJs).
Compensation: USD 88,544 - 207,401 per year. Minimum experience: 10 years.
Responsibilities
- Act as the Agent Engineer for Applied AI, serving as the primary driver for the most critical customer AI initiatives.
- Transform conversational prototypes into production-ready solutions by owning the end-to-end engineering lifecycle and helping move from feasibility to measurable business value.
- Lead delivery for Conversational AI pilots and help establish the first Customer User Journeys (CUJs) for large customers at their sites, with a high-travel, high-impact approach.
- Build evaluation (Eval) pipelines and observability frameworks to optimize complex agentic workloads, with attention to reasoning loops, tool selection, latency, and production-grade security and networking.
- Identify repeatable field patterns and friction points in the Google AAI stack, converting them into reusable modules or feature requests for Engineering teams.
- Co-build with customer engineering teams to introduce Google-grade development best practices to support long-term success and end-user adoption.
- Apply deep expertise across software engineering, Machine Learning Operations, and cloud infrastructure.
Requirements
- 10+ years of experience with software development using Python or similar coding languages.
- Experience serving as the lead developer for complex Conversational AI and CX applications, moving from prototypes to production-grade agentic workflows (including multi-agent systems and MCP servers) that drive measurable ROI.
- Ability to architect and code conversational flows optimized for integration between Google’s 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 infrastructure using Terraform or similar tools to automate setup of agents, functions, or networking.
- Experience building full-stack applications that connect with enterprise IT infrastructure and supporting external customer delivery.
- Experience implementing multi-agent systems using frameworks such as ReAct and self-reflection.
- Strong debugging and optimization skills for agent logic, including tracing conversation IDs across microservices to resolve failures in real time.
- Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to reduce hallucinations.
Technologies
Python, Machine Learning Operations, cloud infrastructure, Google AAI stack, GCP, Terraform, multi-agent systems, MCP servers, ReAct, RAG, microservices, APIs
Benefits
- Paid time off based on employee grade (A-F): Vacation 12-25 days depending on grade, Company paid holidays, Personal Days, and 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
Location
Hybrid role across multiple locations: Atlanta, Nashville, Chicago, Dallas, New Jersey.
