Forward Deployed Engineer
About The Position
Capgemini is seeking a highly motivated Forward Deployed Engineer to work directly with enterprise customers, bridging product engineering, AI, data platforms, and business outcomes. The role combines technical consulting, solution architecture, software development, and stakeholder management to deliver production-grade AI, data, and automation solutions in complex enterprise environments. The position involves deploying scalable AI and data platforms, integrating enterprise systems, and translating customer requirements into robust technical solutions. The engineer works with customers, product teams, architects, and leadership to accelerate adoption, drive innovation, and maximize business value.
Requirements
- Strong software engineering fundamentals and expertise in Java, Python, or modern programming languages.
- Experience designing and deploying cloud-native applications on AWS, Azure, or GCP.
- Strong knowledge of distributed systems, APIs, microservices, and event-driven architectures.
- Experience with AI/ML platforms, Generative AI, LLMs, RAG, Agentic AI, and workflow orchestration frameworks.
- Hands-on experience with data engineering, ETL pipelines, data lakes, and modern analytics platforms.
- Strong understanding of Kubernetes, Docker, CI/CD, DevOps, and Infrastructure as Code.
- Experience integrating enterprise applications such as ERP, CRM, HR, and data platforms.
- Ability to work directly with executive stakeholders, technical leaders, and cross-functional teams.
- Strong problem-solving, communication, and customer-facing consulting skills.
Nice To Haves
- Experience with LangGraph, LangChain, CrewAI, AutoGen, ADK, A2A, MCP, or similar agent frameworks.
- Experience deploying solutions using Google Gemini, Azure OpenAI, OpenAI, Anthropic Claude, or Vertex AI.
- Knowledge of real-time data streaming technologies such as Kafka, Pub/Sub, or Event Hubs.
- Familiarity with vector databases, knowledge graphs, and semantic search architectures.
- Experience in regulated industries such as Healthcare, Banking, Financial Services, or Insurance.
- Exposure to MLOps, LLMOps, model governance, and AI observability platforms.
Responsibilities
- Partner directly with customers to understand business requirements and translate them into scalable technical solutions.
- Design, develop, and deploy AI, data, and cloud-native applications in production environments.
- Build integrations between enterprise systems, APIs, data platforms, and AI services.
- Work across the full solution lifecycle, including discovery, architecture, implementation, deployment, and post-production support.
- Develop proof-of-concepts, pilots, and production-grade solutions that address customer challenges.
- Collaborate with product and engineering teams to influence roadmap decisions based on field insights.
- Troubleshoot complex technical issues and optimize system performance, reliability, and scalability.
- Enable customers through technical workshops, architecture reviews, and best-practice guidance.
- Ensure security, compliance, governance, and operational excellence across deployed solutions.
- Drive successful adoption of AI, automation, and digital transformation initiatives.
Benefits
- Paid time off based on employee grade, including 12–25 vacation 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, such as 401(k) in the U.S. and RRSP in Canada.
- Life and disability insurance.
- Employee assistance programs.
- Other benefits as provided by local policy and eligibility.
- The role may be eligible for variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Education Level
No Education Listed
