Principal Engineer - Context Engineering & LLM Optimization

Job Description

This job is responsible for defining and leading the engineering approach for solutions at the program or portfolio level, to deliver significant business outcomes. Key responsibilities include continuously improving the design, quality, and reuse of the solution and delivering technology enablers that improve development efficiencies for the solution. Job expectations include familiarity with at least one area of engineering, acting as a “go to” reference across the organization, and applying knowledge to improve technical competencies through recruitment and development activities.

Developer Experience (Dev Ex) provides enterprise technical standards and common technical services, platforms, and tools that are leveraged by delivery teams across all lines of business. Within the SDLC Software Delivery Lifecycle program, this role leads portfolio product delivery strategy and execution for enterprise software delivery capabilities, ensuring the right investments, operating model, governance, and prioritization are in place to improve how internal technical users build, test, and deliver software at scale.

The Context Engineering & LLM Optimization Principal Engineer is responsible for designing how information is selected, organized, compressed, prioritized, and presented to LLMs. This role focuses on context window management, prompt architecture, retrieval orchestration, grounding strategies, instruction design, tool‑use patterns, and evaluation of LLM behavior. This engineer ensures that LLM applications receive the right context, in the right format, at the right time, with minimal token waste and maximum answer quality.

• Develops the engineering approach for the entire program/portfolio solution and works with Architecture, to develop/analyze/deliver the implementation of technical enablers
• Leads the planning, definition, and design of the complex features which span multiple teams and explore solution alternatives
• Creates ideas on designing complex technology and solution development approaches
• Leads the technical oversight for teams in solution development including design reviews and code within own domain
• Defines the technology tool stack for the solution within ranged of internally approved and supported technologies
• Explores state-of-the-art technologies to improve development efficiencies, quality of test/QA coverage, and release management
• Leads and is responsible for the end-to-end test strategy/creation/adherence, and the integration between teams for a program/portfolio solution
• Design context engineering strategies for enterprise LLM and RAG applications.
• Define prompt architectures for system prompts, developer instructions, user prompts, retrieved context, tool outputs, conversation history, and structured constraints.
• Optimize context window usage through summarization, compression, ranking, filtering, deduplication, and context prioritization.
• Design retrieval orchestration patterns that determine what data is retrieved, when it is retrieved, and how it is injected into the LLM prompt.
• Partner with RAG database engineers to tune retrieval outputs for downstream reasoning quality.
• Partner with data ingestion engineers to improve source formatting, metadata, and chunk structures for better contextual use.
• Develop patterns for multi-turn conversation memory, session state, user intent preservation, and context refresh.
• Define strategies for grounding, citation handling, source attribution, conflicting evidence resolution, and hallucination reduction.
• Improve the experience for our developers, making it easier to deliver industry-leading solutions, while managing work efficiently and with the right controls
• Advance our technology platforms through innovation
• Reduce risk and improve quality across our technology portfolio by aligning to a single enterprise architecture strategy and delivering governance that enables consistency, integration and automation
• Design LLM evaluation frameworks for answer quality, factuality, instruction adherence, relevance, safety, and token efficiency.
• Establish prompt engineering and context engineering standards across product and…