Forward Deployed AI Engineer

Baker Tilly•San Jose, CA

About The Position

Baker Tilly is seeking a Forward Deployed AI Engineer for the founding team of its AI Product Group (APG) Agent Factory. The role designs, develops, and deploys AI-powered applications and intelligent agentic workflows across Tax, Assurance, and Advisory. It is a hands-on, full-stack engineering position focused on production-ready AI solutions that combine advanced AI capabilities, intuitive user experiences, and practical business workflows. Working directly with firm practitioners and subject matter experts, the engineer translates complex business processes into scalable AI-enabled solutions and builds applications that support professional review and decision-making. As an early member of the AI Product Group, the engineer collaborates with product, design, data, platform engineering, and globally distributed technical teams to deliver solutions from concept through production deployment. The position emphasizes software engineering fundamentals, evaluation-driven development, execution, and business stakeholder collaboration. Baker Tilly is a professional services firm providing advisory, tax, and assurance services. The work location status should be discussed with a Baker Tilly talent acquisition professional. The national and California pay rate range is $205,000–$250,000. Actual compensation depends on relevant factors, and Baker Tilly offers a comprehensive compensation and benefits package to eligible employees.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field.
At least 5 years of hands-on software engineering experience, including success designing, developing, and delivering multiple production-quality applications or products from concept through deployment.
Experience deploying at least one LLM-powered feature or application to real users, regardless of scale.
Experience working directly with domain experts, business stakeholders, or customers to translate requirements into technical solutions and take ownership of delivered outcomes.
Strong full-stack software engineering experience, including backend services, data models, APIs, and modern user-facing applications.
Deep proficiency in at least one mainstream programming language, such as Python, TypeScript, Go, or Java, including knowledge of language fundamentals, design patterns, and production-quality development practices.
Ability to quickly learn and apply new programming languages, frameworks, and technologies.
Strong software engineering fundamentals, including system design, application architecture, automated testing, debugging, performance optimization, and development of scalable, maintainable systems.
Experience developing and integrating modern web applications, APIs, authentication mechanisms, and secure enterprise services.
Ability to validate technical solutions through measurable outcomes, such as automated testing, benchmarks, experiments, evaluation frameworks, or A/B testing.
Strong analytical thinking, technical judgment, and problem-solving skills, including the ability to evaluate trade-offs, resolve ambiguity, and develop practical solutions to complex challenges.
Experience collaborating with nontechnical stakeholders and subject matter experts, and ability to explain technical concepts and recommendations in clear, business-focused language.
Excellent written and verbal communication skills, including documenting technical solutions, articulating design decisions, and collaborating across technical and business teams.
Ability to work independently, manage competing priorities, adapt quickly to evolving requirements, and deliver high-quality solutions in a fast-paced environment.
Experience using AI-assisted and agentic development tools to enhance engineering productivity, or a strong willingness to incorporate these technologies into daily development practices.

Nice To Haves

An advanced degree.
Familiarity with Python and TypeScript.
Familiarity with LLM applications, retrieval-augmented generation (RAG), AI evaluation methodologies, or Model Context Protocol (MCP).
Exposure to agentic AI concepts, including orchestration, tool use, context management, and human-in-the-loop workflows; prior experience building AI agents is not required.
Experience with cloud-based application development and technologies such as Microsoft Azure, containers, PostgreSQL, and React.
Experience in professional services, regulated industries, or environments serving highly specialized business users; prior Tax, Assurance, or Accounting experience is not required.

Responsibilities

Design, develop, implement, and maintain AI agents and multi-step workflows, including task decomposition, orchestration, context and memory management, tool integration, human-in-the-loop checkpoints, and failure handling.
Develop production-quality full-stack applications, backend services, APIs, data models, dashboards, conversational interfaces, and user-facing workflows for AI-powered solutions.
Collaborate with Tax, Assurance, and Advisory professionals and subject matter experts to understand business processes, identify automation opportunities, and turn expertise into requirements and working software.
Establish measurable hypotheses, testing criteria, evaluation frameworks, and performance baselines to validate AI capabilities and guide technical decisions before production deployment.
Build and maintain automated tests, regression suites, and ground-truth datasets with subject matter experts to support reliability, accuracy, and continuous improvement.
Own solutions from development through deployment, monitoring, troubleshooting, and ongoing enhancements, supporting adoption and positive user outcomes.
Integrate AI applications with enterprise systems, APIs, and governed data sources using established integration standards, secure access controls, and data contracts.
Develop and contribute reusable technical patterns, components, documentation, and engineering practices for consistent, scalable Agent Factory development.
Work with external engineering partners to acquire specialized expertise, transition solutions into internally owned production environments, and produce maintainable code, tests, and operational documentation.
Collaborate with U.S. and India engineering teams, product management, design, data platform, and enterprise architecture to align solutions, share knowledge, and maintain consistent engineering standards.
Use user feedback, application performance data, emerging AI technologies, and evaluation results to improve solutions and identify opportunities to enhance productivity, reliability, and business value.
Participate in special projects and perform other duties as assigned to advance the firm's AI engineering capabilities and business priorities.