Context Engineering Manager, Digital Transformation & Innovation

BDO USA

2d

About The Position

The Context Engineering Manager serves as the context and knowledge lead for all Digital Transformation & Innovation (DT&I) product and process development, with a primary emphasis on the knowledge, skill, and instruction infrastructure that AI systems and engineers consume. This role owns the design, governance, and continuous improvement of reusable skill libraries, agent-instruction standards (CLAUDE.md and equivalents), retrieval-grounding corpora, and domain-knowledge encodings that make AI-accelerated delivery reliable, repeatable, and audit-ready across the DT&I product portfolio. The role works in close coordination with the AI Engineering Manager and the Data & Analytics Lead to ensure assurance domain knowledge is captured as high-quality, governed, agent-consumable context. The Context Engineering Manager partners closely with the AI & Digital Innovation Delivery Lead and cross-functional teams to align context-engineering practices, knowledge standards, and product delivery with assurance service delivery objectives, firm policies, and security standards.

Requirements

• High School Diploma/GED, required
• Seven (7) or more years of experience in software, data, or AI engineering, or related technology fields, required
• Three (3) or more years of experience building LLM context, retrieval-augmented generation (RAG), or knowledge-management systems, required
• Two (2) or more years of experience defining reusable engineering assets, developer-enablement tooling, or technical standards, required
• Expert-level knowledge of Microsoft Azure AI services including Azure AI Foundry, Azure OpenAI, and Azure AI Search, required
• Strong understanding of LLM context windows, prompting, retrieval, and grounding, and how each affects accuracy, cost, and reliability, required
• Experience with retrieval and vector technologies (Azure AI Search, embeddings, hybrid search, re-ranking), required
• Extensive knowledge of agent-instruction and skill systems (CLAUDE.md and equivalents) and Markdown-based knowledge structures, required
• Expert-level knowledge of context engineering, retrieval design, and grounding for production LLM systems.
• Proven ability to serve as a hands-on context architect while providing standards, governance, and team enablement.
• Deep knowledge of information architecture and the ability to translate subject-matter expertise into machine-consumable knowledge.
• Familiarity with AI application and agent runtimes and the ability to collaborate with engineering teams on context dependencies.
• Excellent problem-solving skills with a focus on accuracy, reliability, and grounding quality.
• Strong communication skills with the ability to convey technical concepts to non-technical stakeholders and leadership.
• Experience presenting context and AI governance recommendations to governance bodies (e.g., Architecture Review Boards).
• Strong knowledge of data privacy, security, and compliance considerations for AI and knowledge systems.
• Ability to work across technical teams and business stakeholders in complex, fast-paced enterprise environments.
• Self-directed with the ability to manage multiple priorities and competing deadlines.
• Collaborative mindset with the ability to build relationships across all levels of the organization.

Nice To Haves

• Bachelor’s degree with a focus in Computer Science, Information Systems, Engineering, Information Technology, preferred
• Experience extracting and codifying domain knowledge into machine-consumable formats, preferred
• Experience delivering enterprise-scale AI or knowledge solutions in professional services, assurance, or accounting industries, preferred
• Experience with context governance, prompt management, or AI evaluation frameworks, preferred
• Microsoft Certified: Azure AI Engineer Associate, or equivalent, preferred
• Experience with agentic development tooling (Claude Code or equivalent) and Git-based workflows, preferred
• Experience with .NET/C# and/or Python for context and evaluation tooling, preferred
• Experience with AI evaluation and observability tooling, preferred

Responsibilities

• Designs and maintains the firm’s context infrastructure including hierarchical skill libraries (foundation and archetype layers) and agent-instruction standards (CLAUDE.md and equivalents) with defined inheritance, ownership, and versioning.
• Serves as the principal technical authority on prompt and context patterns, reusable scaffolding, and context-as-code discipline across the DT&I portfolio.
• Defines how assurance domain knowledge is captured, structured, and surfaced to AI systems, and codifies BDO methodology (AKB) into retrievable, governed knowledge.
• Evaluates and integrates emerging context-engineering tools, frameworks, and knowledge platforms to continuously improve grounding quality and developer enablement.
• Designs context evaluation, provenance tracking, and citation discipline to ensure traceable, trustworthy grounded outputs.
• Owns retrieval-corpus curation and grounding quality including source selection, chunking strategy, embeddings, and index design using Azure AI Search and vector stores.
• Designs and tunes retrieval pipelines (hybrid search, re-ranking, metadata filtering) for accuracy, cost, and latency across DT&I products.
• Establishes corpus lifecycle management including freshness, versioning, deduplication, and retirement of stale knowledge.
• Partners with the AI Engineering Manager to integrate grounded context into agent and application runtimes.
• Implements grounding evaluation, regression testing, and quality metrics for retrieval-augmented features.
• Governs the skill and context catalog as a managed asset with named ownership, review cadence, and change control consistent with the Advantage SDLC and Architecture Review Board.
• Provides governed context scaffolding and standards for the Advantage Forge citizen-engineer program and product teams.
• Coaches engineers on context-engineering practice and maintains documentation so AI-native development scales across the practice.
• Defines standards for token economics, context-window management, and prompt efficiency across the portfolio.
• Ensures context infrastructure and grounded knowledge comply with firm security policies, privacy requirements, and regulatory standards (SOC 2, PCAOB AS 2201, QC 1000, ISO 27001).
• Prevents sensitive or restricted data from entering prompts, corpora, or model context, and maintains auditability and traceability of grounded knowledge.
• Partners with risk and compliance stakeholders to maintain alignment between context infrastructure and firm governance requirements.
• Performs other duties as assigned.
• Willingly accepts share of less desirable assignments.
• Acts as a direct supervisor to engineering and development team members, as assigned.
• Acts as a career advisor and mentor to engineering and development team members as assigned.

Benefits

• Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: High school or GED