Principal Platform Engineer

Overview

Baker Tilly is a leading advisory, tax and assurance firm, providing clients with a genuine coast-to-coast and global advantage in major regions of the U.S. and in many of the world’s leading financial centers – New York, London, San Francisco, Los Angeles, Chicago and Boston. Baker Tilly Advisory Group, LP and Baker Tilly US, LLP (Baker Tilly) provide professional services through an alternative practice structure in accordance with the AICPA Code of Professional Conduct and applicable laws, regulations and professional standards. Baker Tilly US, LLP is a licensed independent CPA firm that provides attest services to its clients. Baker Tilly Advisory Group, LP and its subsidiary entities provide tax and business advisory services to their clients. Baker Tilly Advisory Group, LP and its subsidiary entities are not licensed CPA firms.

Baker Tilly Advisory Group, LP and Baker Tilly US, LLP, trading as Baker Tilly, are independent members of Baker Tilly International, a worldwide network of independent accounting and business advisory firms in 141 territories, with 43,000 professionals and a combined worldwide revenue of $5.2 billion. Visit bakertilly.com or join the conversation on LinkedIn, Facebook and Instagram.

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Job Description:

Baker Tilly is seeking a Principal Platform Engineer — Integrations to lead the design, development, and operation of the firm's AI agent integration framework within the APG platform. This role is responsible for establishing scalable, secure, and standardized integration capabilities that connect third-party AI agents to the firm's technology ecosystem while maintaining ownership and control of enterprise data, decision history, and learning. The position plays a critical role in defining and enforcing vendor integration standards, building event-driven interfaces and data ingestion pipelines, and ensuring interoperability, portability, and production readiness across AI-enabled solutions.

As a foundational member of the Platform & Production Engineering team, this individual will partner closely with architecture, engineering, data platform, procurement, and vendor teams to translate integration requirements into production-ready solutions. The ideal candidate brings deep technical expertise in platform engineering, API and event-driven architectures, vendor integration, and observability, combined with strong hands-on development skills and the ability to establish technical standards in a rapidly evolving AI environment.

Responsibilities

• •Design and Build Integration Frameworks: Develop and maintain scalable integration capabilities, including event-driven architectures, publish/subscribe interfaces, webhooks, APIs, and Model Context Protocol (MCP) endpoints that enable secure, standardized connectivity between third-party AI agents and the firm's platform.
• •Establish and Enforce Vendor Integration Standards: Define and maintain vendor-facing technical specifications, integration requirements, and acceptance criteria, ensuring third-party solutions meet established standards for interoperability, security, portability, and performance.
• •Support Vendor Contract Requirements: Partner with procurement, legal, and architecture teams to translate technical integration standards into measurable, testable contractual commitments, including requirements for data ownership, decision traces, export rights, and vendor portability.
• •Develop Data Ingestion and Telemetry Pipelines: Build and operate pipelines that capture AI agent decision traces, lineage, activity data, and telemetry, integrating this information into the firm's data platform and Intelligence Layer to support monitoring, evaluation, and continuous improvement.
• •Ensure Secure Integration and Access Controls: Implement identity management, entitlements, permissible-use controls, and secure integration boundaries that protect enterprise information and prevent unauthorized system interactions.
• •Advance Platform Engineering Capabilities: Collaborate with the Chief Architect and platform engineering leadership to develop shared platform services, including gateways, runtime capabilities, and reusable infrastructure that support the firm's expanding AI ecosystem.
• •Drive Production Readiness and Reliability: Establish observability, monitoring, testing, and rollback capabilities to ensure integrated AI agents operate reliably, securely, and effectively in production environments.
• •Lead Technical Vendor Integration: Coordinate directly with external engineering teams to support integration development, technical validation, troubleshooting, and acceptance testing, including the integration of assurance-related AI agent solutions.
• •Collaborate Across Global Engineering Teams: Partner with platform and MLOps engineers in India and cross-functional teams to align technical standards, coordinate development activities, and support consistent engineering practices and operational execution.
• •Support Strategic Initiatives: Participate in special projects and perform other duties as assigned to advance the firm's AI platform strategy and business priorities.

Qualifications

• •Bachelor's degree in Computer Science, Engineering, or a related field,; advanced degree preferred.
• •10+ years of progressive experience in platform engineering, systems integration, or related software engineering disciplines, including development and support of production-scale enterprise solutions.
• •Demonstrated experience designing, building, and operating event-driven integration architectures, including publish/subscribe messaging, webhooks, API platforms, and distributed systems.
• •Strong hands-on programming experience with Python and/or TypeScript, including recent experience developing, testing, and maintaining production-quality code.
• •Proven experience developing vendor-facing technical specifications, establishing integration standards, and holding external engineering teams accountable for technical requirements and acceptance criteria.
• •Deep understanding of API design, versioning, contract testing, integration patterns, and emerging agent interoperability technologies, including Model Context Protocol (MCP).
• •Experience implementing identity management, authentication, authorization, entitlements, and permissible-use controls within enterprise integration environments.
• •Demonstrated experience building telemetry, event processing, and data ingestion pipelines that integrate with modern enterprise data platforms, including Databricks or comparable lakehouse technologies.
• •Strong knowledge of observability, monitoring, logging, distributed tracing, incident management, and rollback strategies for production systems and third-party integrations.
• •Experience designing integration architectures that support vendor portability, system interoperability, data ownership, and replacement of third-party technology components.
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