Experienced Senior Context Engineer, Digital Transformation & Innovation

BDO USA

About The Position

The Experienced Senior Context Engineer is a senior hands-on software engineer who designs and builds reusable context assets for BDO Advantage’s AI-native product and process development. The role develops, tests, reviews, and ships production code in C#/.NET and Python on the Advantage Azure platform, and leads complex context and knowledge work—including skill libraries, agent-instruction standards, prompt and context patterns, and retrieval-grounding corpora. The engineer establishes conventions and quality standards, works autonomously, mentors junior and mid-level engineers, and partners with the AI Engineering Manager and product teams to capture assurance-domain knowledge as governed, agent-consumable context and deliver it in working applications. The position reports to the Context Engineering Manager and operates within the Advantage SDLC, firm policies, and security standards. The role designs and maintains application services, APIs, and tooling for context assets; sets engineering practices for Git workflows, reviews, testing, and CI/CD; and builds and tunes retrieval pipelines and corpora. It defines evaluation and quality measures for context and grounding, contributes standards for the Advantage Forge citizen-engineer program, and provides technical leadership and mentorship. The engineer follows security, privacy, and compliance requirements and ensures sensitive or restricted data is not included in prompts, corpora, or model context. Travel may be required up to 10%; relocation is not required.

Requirements

High School Diploma/GED.
At least five years of hands-on professional software development experience building, testing, and deploying production applications or services in C#/.NET or Python.
At least three years of experience building LLM-powered features—such as retrieval-augmented generation, agent tooling, or prompt and context systems—that reached production users.
Experience leading the end-to-end design of at least one production service or application, from requirements through deployment and operation in Microsoft Azure.
Experience defining reusable engineering assets, patterns, or technical standards adopted by other engineers.
Proficiency in C#/.NET or Python, including automated testing, dependency management, and performance debugging.
Strong knowledge of Git-based workflows, pull-request review, and CI/CD pipelines using Azure DevOps or GitHub Actions.
Strong knowledge of Microsoft Azure AI services, including Azure AI Foundry, Azure OpenAI, and Azure AI Search.
Strong understanding of LLM context windows, prompting, retrieval, and grounding, and their effects on accuracy, cost, and reliability.
Experience with retrieval and vector technologies, including embeddings, hybrid search, re-ranking, and indexing.
Experience with agent-instruction and skill systems such as CLAUDE.md and equivalents, agentic development tooling such as Claude Code or equivalent, and Markdown-based knowledge structures.
Ability to design, build, debug, and ship working software independently and explain technical decisions clearly in a live, hands-on setting.
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 focused on accuracy, reliability, and grounding quality.
Strong communication skills for explaining technical concepts to technical and non-technical audiences.
Self-directed ability to manage multiple priorities and competing deadlines.
Collaborative mindset and ability to build relationships across teams.

Nice To Haves

Bachelor’s degree focused in Computer Science, Information Systems, Engineering, or Information Technology.
Experience mentoring or providing technical guidance to other engineers.
Experience delivering AI or knowledge solutions in professional services, assurance, or accounting industries.
Microsoft Certified: Azure AI Engineer Associate, or equivalent.
Experience with Azure Container Apps, Semantic Kernel, and Dapr.

Responsibilities

Design, write, test, and ship production code in C#/.NET and/or Python that integrates governed context, retrieval, and agent capabilities into Advantage applications.
Design services, APIs, and tooling to load, validate, version, and serve context assets to agents and applications on Azure Container Apps and Azure AI Foundry, considering reliability, observability, and cost.
Set and enforce team practices for Git workflows, pull-request review, automated testing, and CI/CD pipelines using Azure DevOps or GitHub.
Use agentic development tooling such as Claude Code or equivalent as part of daily delivery.
Review other engineers’ code and context contributions for correctness, quality, security, and reuse.
Design and build reusable context assets, including skill libraries, agent-instruction files, and prompt and context patterns.
Establish team conventions for context-as-code practice, inheritance, and versioning.
Codify BDO assurance domain knowledge into structured, retrievable, governed knowledge with appropriate provenance and citation discipline.
Evaluate and pilot context-engineering tools and frameworks to improve grounding quality and developer productivity.
Design and tune retrieval pipelines, including document parsing, chunking, embeddings, hybrid search, re-ranking, and metadata filtering, for accuracy, cost, and latency.
Manage retrieval-corpus curation and lifecycle, including source selection, freshness, versioning, and retirement of stale knowledge.
Build grounding evaluation, regression testing, and quality metrics for retrieval-augmented features.
Define and run evaluations for context quality and grounding fidelity across products.
Contribute context scaffolding and standards for the Advantage Forge citizen-engineer program and product teams.
Mentor junior and mid-level engineers in software engineering and context-engineering practices and maintain team documentation.
Follow firm security, privacy, and compliance standards when building application code and context assets.
Prevent sensitive or restricted data from entering prompts, corpora, or model context and maintain traceability of grounded knowledge.
Provide technical leadership and mentorship to engineering and development team members, as assigned.
Review and provide feedback on other engineers’ work, as assigned.
Perform other duties as assigned and willingly accept a share of less desirable assignments.