Associate, Forward Deployed Engineer

About the Role

KPMG Advisory practice is seeking an Associate, Forward Deployed Engineer to join our Advisory Services practice.

Key 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.

Requirements & Tech Stack

• Minimum one years of recent experience in software engineering with demonstrated success in building, testing, and shipping production AI, machine learning, or data-intensive applications.
• 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 modern 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.
• Domestic travel required.

Qualifications

• Master's degree from an accredited college or university in computer science, engineering, artificial intelligence, or a related technical field is preferred; minimum of a Bachelor's degree is required.