Note: The job is a remote job and is open to candidates in USA. KPMG US is seeking a Forward Deployed Engineer to build and deploy production-grade generative AI systems and applications. The role involves designing AI agents and orchestration patterns, developing RAG and context engineering workflows, deploying scalable AI services, and ensuring software quality through testing, evaluation, and agile development practices.
Responsibilities
- Rapidly build and deploy end-to-end AI systems and core components of generative AI solutions, owning the full arc from problem framing and MVP development to deployed workflow with a bias to action
- Collaborate with technical leads, product managers, and cross-functional teams to contribute to the technical design of AI agents, orchestration patterns, and advanced context engineering modules
- Drive product advancements by developing robust RAG pipelines, context engineering workflows, and integrations with services like Azure AI Search and Databricks
- Champion production discipline by implementing rigorous testing and evaluation frameworks, including golden sets, regression harnesses, and red-teaming to ensure secure, observable, and auditable code
- Deliver in a fast-paced, outcome-accountable environment, operating in two-to-six-week cycles with direct client and stakeholder feedback to ensure solutions solve real-world problems and are ready for scale
- Deploy and maintain scalable AI microservices and containerized workloads, optimizing performance and reliability to meet enterprise standards
- Champion the use of modern development accelerators such as Claude Code, Lovable, Cursor, and others where policy permits, to increase delivery capacity and velocity while elevating code quality
- Ensure software reliability and high code quality by writing unit tests, participating in code reviews, and utilizing CI/CD pipelines for automated builds and deployments
- Engage in agile development processes including daily stand-ups, sprint planning, and retrospectives
- Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment
Skills
- Minimum three years of recent experience in software engineering with demonstrated success in building, testing, and shipping production AI, machine learning, or data-intensive applications
- Minimum of a high school diploma or GED is required
- Strong programming skills in Python; hands-on experience with modern AI/ML frameworks such as LangChain, LlamaIndex, or Semantic Kernel
- Practical knowledge of modern AI methodologies and engineering practices, including AI systems judgment, context engineering, agentic workflows, and evaluation discipline
- Skilled within an agile environment using SDLC tools like Azure DevOps, Git, and CI/CD pipelines for automated builds and deployments
- Solid experience with cloud platforms, preferably Azure (or GCP/AWS); familiar with containerization technologies like Docker and Kubernetes
- Familiarity with AI-first developer accelerators (such as Cursor, Claude Code, or Copilot) to drive high-velocity development
- Excellent analytical, problem-solving, and communication skills; able to communicate technical ideas clearly, thrive in ambiguous environments, and collaborate effectively with diverse stakeholders
- Ability to demonstrate prior experience with real work via a portfolio, a GitHub repository, or a structured walk-through of a system designed and shipped
- All applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)
- Bachelor's degree from an accredited college or university in computer science, engineering, artificial intelligence, or a related technical field is preferred
- Certifications in areas such as Claude Certified Architect, Claude Certified Developer, OpenAI Codex Deployment Practitioner, and OpenAI Codex Professional are preferred
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