Associate, Forward Deployed Engineer

The KPMG Advisory practice is at the forefront of transformation, offering excellent opportunities for individuals to advance their careers and expertise with KPMG. Looking ahead, we anticipate continued evolution and success within the practice, fostering both personal and professional development, thereby creating new pathways for growth. In this ever-changing market environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture.

At KPMG, our people are our number one priority. With a wealth of learning and career development opportunities, a world-class training facility, and leading market tools, we help our people continue to grow both professionally and personally. If you're looking for a firm with a strong team connection where you can be your whole self, have an impact, advance your skills, deepen your experiences, and have the flexibility and access to constantly find new areas of inspiration and expand your capabilities, then consider a career in Advisory.

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

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

Qualifications:

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

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

Strong programming skills in Python; hands-on experience with modern AI/ML frameworks such as Lang Chain, Llama Index, 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 Dev Ops, 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 Git Hub repository, or a structured walk-through of a system designed and shipped

Domestic travel required

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.…