2 days ago
Base Salary
$170k - $200k/yr
Responsibilities
- Partner with enterprise customers to understand requirements and translate them into scalable technical solutions.
- Design, develop, and deploy AI, data, automation, and cloud-native applications in production.
- Build integrations across enterprise systems, APIs, data platforms, and AI services.
- Own solution lifecycles from discovery and architecture through implementation, deployment, and post-production support.
- Develop proofs of concept, pilots, and production-grade customer solutions.
- Collaborate with product and engineering teams to influence roadmap decisions based on field insights.
- Troubleshoot complex issues and optimize system performance, reliability, and scalability.
- Conduct technical workshops, architecture reviews, and best-practice enablement for customers.
- Ensure security, compliance, governance, and operational excellence across deployed solutions.
- Drive adoption of AI, automation, and digital transformation initiatives.
Requirements
- Strong software engineering fundamentals with 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 with executive stakeholders, technical leaders, and cross-functional teams.
- Strong problem-solving, communication, and customer-facing consulting skills.
- Preferred experience with LangGraph, LangChain, CrewAI, AutoGen, ADK, A2A, MCP, or similar agent frameworks.
- Preferred experience deploying Google Gemini, Azure OpenAI, OpenAI, Anthropic Claude, or Vertex AI solutions.
- Preferred knowledge of Kafka, Pub/Sub, Event Hubs, vector databases, knowledge graphs, and semantic search architectures.
- Preferred experience in Healthcare, Banking, Financial Services, or Insurance.
- Preferred exposure to MLOps, LLMOps, model governance, and AI observability platforms.
Benefits
- Base benefits may include paid time off, 12–25 vacation days depending on employee grade, company 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 and employee assistance programs.
- Additional benefits are provided according to local policy and eligibility for regular full-time employees.
Categories
Forward Deployed
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.