> Markdown version of [/jobs/ext/1954865-systems-engineering-advisor](https://www.wearedevelopers.com/jobs/ext/1954865-systems-engineering-advisor). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Systems Engineering, Advisor - **Company:** Peraton Inc - **Location:** Reston, VA, United States - **Experience:** Experienced - **Salary:** $104,000.0 - $166,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Systems Engineering, Automation of Tests, Microsoft Azure, Continuous Integration, Python (Programming Language), Toolchain, Management of Software Versions, Feature Engineering, Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Machine Learning Operations, GPT, Databricks - **Published:** August 6, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17836935?backUrl=%2Fcareer%2F17836935%2FSystems-Engineering-Advisor-Virginia-Reston ## About the Role Minimum of 8 years with BS/BA; Minimum of 6 years with MS/MA; Minimum of 3 years with PhD, Deep expertise in LLM architectures, transformer models, and modern generative AI techniques. * Demonstrated experience leading finetuning efforts, parameterefficient training, and advanced prompt engineering. * Proven ability to design and implement endtoend RAG pipelines, including embedding workflows, retrieval optimization, and vector database integrations. * Handson experience with one or more LLM frameworks or orchestration toolchains (such as LangChain, LlamaIndex). * Strong Python development skills and experience with distributed compute or GPUaccelerated training environments. * Experience architecting and deploying AI/ML or LLM workflows within cloud platforms such as Azure, AWS, or GCP. * Solid understanding of MLOps/LLMOps practices, including versioning, CI/CD, automated testing, monitoring, and model governance. * Ability to lead technical discussions, mentor team members, and communicate complex AI concepts to diverse audiences. * Ability to obtain/maintain a Public Trust clearance Preferred Skills: * Experience implementing multiagent or agentic AI systems for task automation and reasoning. * Familiarity with LLM evaluation frameworks, structured benchmarking, or humanintheloop refinement methods (e.g., RLHFstyle workflows). * Expertise with advanced retrieval techniques such as hybrid search, graph retrieval, or longcontext optimization. * Experience optimizing model inference through quantization, model compression, or model distillation. * Background integrating LLM services with largescale analytics environments (e.g., Databricks, Snowflake, Spark). * Strong skills in exploratory data analysis, feature engineering, and data modeling to support domainspecific LLM customization. * Experience developing innovative prototypes or POCs that leverage stateoftheart generative AI approaches. * Exposure to emerging architectures such as mixtureofexperts models, longcontext transformers, or experimental generative frameworks. ## Description The LLM Specialist will drive the design, development, and operationalization of advanced largelanguagemodel capabilities across a cloudbased analytics ecosystem. This role leads innovation efforts around cuttingedge AI, owning the architecture and strategy for finetuning, retrievalaugmented generation (RAG), agentic frameworks, and domainspecific model adaptation. The specialist will guide the development of highimpact prototypes, oversee the evolution of scalable LLM pipelines, and ensure robust governance, security, and performance across all model implementations. Partnering with engineering, product, and data teams, this position provides technical leadership, evaluates emerging LLM technologies, sets best practices, and helps drive transformation through the practical, safe, and effective deployment of generative AI. ## Related Videos - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Speeding up Web Apps performance with WebAssembly and Emscripten](https://www.wearedevelopers.com/videos/1985-speeding-up-web-apps-performance-with-webassembly-and-emscripten) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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