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Capgemini Sogeti

Senior Forward Deployed Engineer - Lead Software Engineer

Capgemini Sogeti
Atlanta, GA $89k - $207k/yr Full time Posted 1d ago
Backend Developer Senior Agentic Ai Ai Agent Ai Agent Platform APIs Application Security Artificial Intelligence Automation Cloud Cloud Infrastructure Cloud Native Cloud Operations Cloud Platform Cloud Platforms Cloud Technology Data Analysis DevOps DevSecOps Engineering Facilities Management Generative AI Google Cloud Information Technology (IT) Infrastructure As Code Machine Learning Operations Management Model Evaluation Programming Programming Language Programming Languages Project Management Rag Architectures Security Security Automation Software Engineer Software Engineering Software Security
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Job Description

Capgemini Sogeti offers the support and structure to help engineering leaders deliver meaningful, real-world AI outcomes. This hybrid role spans multiple locations including Atlanta, Nashville, Chicago, Dallas, and New Jersey, with benefits designed to support your health, stability, and time away.

As a Senior Forward Deployed Engineer in Applied AI, you will act as the primary driver for customers’ most critical AI initiatives. You will own end-to-end engineering from early conversational prototypes through production-ready, scalable, and secure agentic workflows, including the initial Customer User Journeys (CUJs) deployed at customer sites.

What you’ll do

  • Own the end-to-end engineering lifecycle for conversational AI solutions, moving from initial demonstrations to scalable, production-grade business value and secure deployments.
  • Lead technical delivery for Conversational AI pilots and help establish the first Customer User Journeys (CUJs) for major customers at their sites.
  • Develop evaluation (Eval) pipelines and observability frameworks to optimize agentic workloads, with emphasis on reasoning loops, tool selection, and reducing latency while maintaining security and networking requirements.
  • Spot repeatable field patterns and technical friction points across the Google AAI stack, then turn them into reusable modules or engineering feature requests.
  • Co-build with customer engineering teams to apply Google-grade development best practices that support long-term success and strong end-user adoption.
  • Serve as lead developer for complex Conversational AI and CX applications, progressing from rapid prototypes to production-ready agentic workflows (including multi-agent systems and MCP servers) that support measurable ROI.
  • Architect and code conversational flows that connect Google Conversational AI products to 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 failures in real time.
  • Connect agents to enterprise knowledge bases and optimize RAG chunking to reduce hallucinations.

What you bring

  • 10+ years of software development experience using Python or similar coding languages.
  • Experience leading the development of complex Conversational AI and CX applications, transitioning from prototypes to production-ready agentic workflows such as multi-agent systems and MCP servers.
  • Experience architecting and coding conversational flows integrated with live customer infrastructure, including APIs, legacy data silos, and security perimeters.
  • Experience architecting AI systems on cloud platforms (e.g., GCP).
  • Experience deploying resources via Terraform or similar tools to automate setup of agents, functions, and networking.
  • Experience building full-stack applications that interact with enterprise IT infrastructure and supporting external customer projects.
  • Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
  • Experience debugging agent logic and optimizing tool selection, including tracing conversation IDs across microservices for real-time failure resolution.
  • Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking.

Technology focus

  • Python, Google AAI stack, Machine Learning Operations (MLOps), GCP, Terraform, MCP servers, multi-agent systems, ReAct, self-reflection, RAG

Hybrid location

Atlanta, GA (hybrid) with a hybrid footprint across multiple locations: Atlanta, Nashville, Chicago, Dallas, and New Jersey.

Compensation

The base compensation range for this role in the posted location is $88,544 - $207,401 per year.

Benefits

  • Paid time off based on employee grade (A-F): Vacation 12-25 days depending on grade, plus company paid holidays, Personal Days, and Sick Leave.
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada).
  • Life and disability insurance.
  • Employee assistance programs.
  • Other benefits provided by local policy and eligibility (U.S. and Canada).

This is a high-travel, high-impact role focused on leading technical delivery for Conversational AI pilots and establishing the first Customer User Journeys (CUJs) for the largest customers at their sites.

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