BDO RISE is hiring for Digital Delivery Manager - Associate Director

Job Summary:

This role is part of a peer leadership group with the Context Engineering Manager, who owns the context layer, and the AI Engineering Manager, who owns AI application and agent runtime. Together, the three leaders share ownership of the delivery platform, engineering standards, agentic pipeline, and shared skill and agent library. Each leader is also accountable for delivery in the product lanes assigned to their team. The role operates within the Advantage SDLC, ARB, firm policies, and security standards, and helps keep the practice aligned to one shared platform rather than allowing parallel stacks to form.

Duties & Responsibilities

• Agentic Delivery Operations — Co-own and improve the shared agentic delivery pipeline with DT&I peers. Break work into units that agents can execute, with clear entry criteria, exit criteria, and verification steps. Contribute reusable agents, skills, and tooling back to the shared library, and track throughput per agent-hour, human review load, rework rate, and cost per delivered increment.
• Context Engineering Practice — Lead the RISE context engineering team and co-develop practice standards with the Context Engineering Manager. These standards include context and prompt versioning, session and handoff artifact design, agent instruction inheritance such as CLAUDE.md and equivalents, context window management, and prevention of context drift across long-running work. Maintain change control over agents, prompts, context packages, and tool definitions as governed configuration items.
• Validation, Evaluation & Quality Assurance — Own verification of agent-produced work products, including the evidence required, the accountable attester, the audit trail, and the steps a reviewer must follow to reconstruct how an output was produced. Build and maintain golden data sets, regression suites, adversarial coverage, drift detection, and evaluation-based release gates. Keep the deterministic and probabilistic boundary explicit in every design.
• Product & Platform Engineering Delivery — Deliver assigned features across the Advantage product portfolio on the .NET 10 / React stack, integrating Azure AI Foundry, Semantic Kernel, Azure OpenAI, Azure AI Search, Azure Container Apps, Dapr, and Microsoft Fabric. Take designs through the pre-build design review panel before pipeline entry and supply reviewers to it, and own CI/CD, testing, observability, and production support for what the team ships.
• Team Leadership & Capability Building — Build and mentor a RISE team of context engineers, evaluation engineers, and AI and full-stack engineers. Establish role clarity, performance expectations, and career paths for disciplines new to the firm, and staff for depth over headcount so capability growth shows up as throughput rather than team size.
• Risk Management — Ensure solutions and the agents that produce them meet firm security, privacy, and compliance baselines (SOC 2, PCAOB AS 2201, QC 1000, ISO 27001); define human-in-the-loop review as a documented control covering review depth, reviewer qualification, sign-off evidence, and exception escalation; and lead root cause analysis and corrective action for defects, agent failures, and control gaps.Supervisory Responsibilities

This role manages context engineers, evaluation engineers, and AI and full-stack engineers within RISE, and may direct contract resources. The role helps set DT&I engineering practice as a peer of the Context Engineering Manager and AI Engineering Manager, reviews code and evaluation results, and is accountable for the quality and reliability of what the RISE team ships to production. Portfolio priorities are set jointly with those peers and the AI & Digital Innovation Delivery Lead.

Success in this role is measured by reliable delivery of assigned product increments, improved throughput through agentic delivery, reduced rework, strong evaluation coverage, compliant production releases, and sustained use of the shared Advantage platform and engineering standards.

Qualifications

Key stakeholders include DT&I engineering peers, Assurance leadership, AI and digital innovation delivery leadership, infrastructure, data, security, compliance, and product stakeholders across RISE and BDO USA.

• Education: Bachelor’s degree in computer science, Information Systems, Engineering, or a related field required; Master’s degree is preferred.
• Experience: Twelve (12-15) or more years in software, Data, or AI engineering, including five (5) or more years in Engineering Leadership, three (3) or more years in building Production AI, LLM, RAG, and/or Multi-Agent Systems beyond single-prompt applications, five (5) or more years of experience in leading large Program/Portfolio delivery and three (3) or more years of experience in Budget, Vendor & stakeholder Management. Demonstrated experience designing evaluation and validation approaches for non-deterministic systems, including regression testing and quality gating, required. Regulated or Professional Services experience is preferred.
• License / Certification: Relevant Azure or AI certification preferred (e.g., Microsoft Certified: Azure AI Engineer Associate).
• Software: Azure AI Foundry, Semantic Kernel, Azure OpenAI / model APIs, Azure AI Search / vector stores, Azure Container Apps and Dapr, Microsoft Fabric, .NET / C#, React and TypeScript, Azure DevOps / CI-CD, evaluation and observability tooling, and Claude Code or equivalent agentic development tooling.Other Knowledge, Skills & Abilities
• Deep working knowledge of LLM context windows, prompting, retrieval, grounding, and multi-agent coordination, and how each affects accuracy, cost, and reliability.
• Evaluation and measurement mindset; able to define and defend accuracy, cost, and latency targets, and to evidence them under audit-grade scrutiny.
• Production-grade software discipline: testing, CI/CD, observability, and reliability in a governed environment.
• Builds shared standards with peers and extends a common platform rather than forking it locally, including comfort with adversarial design review in both directions.
• Clear communication and pragmatic delivery focus; partners across context, AI, infrastructure, data, and assurance stakeholders with meaningful daily overlap with U.S. hours.