Job Summary:
The Experienced Senior Context Engineer is a senior individual contributor responsible for designing and building the reusable context assets that power BDO Advantage's AI-native product and process development. This role owns complex context and knowledge work-skill libraries, agent-instruction standards (CLAUDE.md and equivalents), prompt and context patterns, and retrieval-grounding corpora-and establishes conventions and quality standards that other engineers follow. The Experienced Senior Context Engineer works with a high degree of autonomy, provides technical guidance and mentorship to junior and mid-level engineers, and partners closely with the AI Engineering Manager and product teams to ensure assurance domain knowledge is captured as high-quality, governed, agent-consumable context. The role reports to the Context Engineering Manager and operates within the Advantage SDLC, firm policies, and security standards.
Job Duties:
Context & Knowledge Engineering
Designs and builds complex, reusable context assets-skill libraries, agent-instruction files (CLAUDE.md and equivalents), and prompt and context patterns-for use across DT&I products
Serves as a senior technical resource on context-as-code practice, establishing conventions, inheritance, and versioning standards for the team
Codifies BDO assurance domain knowledge (AKB) into structured, retrievable, governed knowledge with appropriate provenance and citation discipline
Reviews context and skill contributions from other engineers for quality, security, and reuse
Evaluates and pilots emerging context-engineering tools and frameworks to improve grounding quality and developer productivity
Retrieval & Grounding Engineering
Designs and tunes retrieval pipelines (chunking strategy, embeddings, hybrid search, re-ranking, metadata filtering) for accuracy, cost, and latency using Azure AI Search and vector stores
Owns retrieval-corpus curation and lifecycle management including source selection, freshness, versioning, and retirement of stale knowledge
Builds grounding evaluation, regression testing, and quality metrics for retrieval-augmented features
Context Quality, Evaluation & Enablement
Defines and runs evaluation for context quality and grounding fidelity across products
Contributes context scaffolding and standards for the Advantage Forge citizen-engineer program and product teams
Mentors junior and mid-level engineers on context-engineering practice and maintains team documentation
Risk Management
Ensures context assets and grounded knowledge comply with firm security, privacy, 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 traceability of grounded knowledge
Performs other duties as assigned
Willingly accepts share of less desirable assignments
Supervisory Responsibilities:
Provides technical leadership and mentorship to engineering and development team members, as assigned
Reviews and provides feedback on the work of other engineers, as assigned
Qualifications, Knowledge, Skills, and Abilities:
Education:
High School Diploma/GED, required
Bachelor's degree with a focus in Computer Science, Information Systems, Engineering, Information Technology, preferred
Experience:
Five (5) 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
Experience defining reusable engineering assets, patterns, or technical standards, required
Experience mentoring or providing technical guidance to other engineers, preferred
Experience delivering AI or knowledge solutions in professional services, assurance, or accounting industries, preferred
License/Certifications:
Microsoft Certified: Azure AI Engineer Associate, or equivalent, preferred
Technology:
Strong 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 (embeddings, hybrid search, re-ranking, indexing), required
Experience with agent-instruction and skill systems (CLAUDE.md and equivalents) and Markdown-based knowledge structures, required
Experience with agentic development tooling (Claude Code or equivalent), Git-based workflows, and .NET/C# and/or Python, preferred
Knowledge, Skills, & Abilities:
Deep knowledge of context engineering, retrieval design, and grounding for production LLM systems
Ability to work independently on complex, ambiguous problems and provide technical guidance to others
Ability to translate subject-matter expertise into machine-consumable knowledge
Excellent problem-solving skills with a focus on accuracy, reliability, and grounding quality
Strong communication skills with the ability to convey technical concepts to technical and non-technical audiences
Self-directed with the ability to manage multiple priorities and competing deadlines
Collaborative mindset with the ability to build relationships across teams
Ability to travel up to 10%, no relocation required
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.
National Range: $110,000 - $140,000
Maryland Range: $110,000 - $140,000
NYC/Long Island/Westchester Range: $110,000 - $140,000
All qualified applicants will receive consideration for employment without regard to race, age, color, religion, sex, national origin, disability, protected veteran status, or any other classification protected by law.
