External Job Posting Title Senior Systems Engineer

Responsibilities The Senior Systems Engineer will drive the design, development, and operationalization of advanced large‑language‑model capabilities across a cloud‑based analytics ecosystem. What you'll do: Lead innovation efforts around cutting‑edge AI, owning the architecture and strategy for fine‑tuning, retrieval‑augmented generation (RAG), agentic frameworks, and domain‑specific model adaptation. Guide the development of high‑impact prototypes, oversee the evolution of scalable LLM pipelines, and ensure robust governance, security, and performance across all model implementations. Partner 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. Qualifications Mandatory Qualifications: 4 years with AS/AA; 2 years with BS/BA; 0 years with MS/MA; 6 years with HS Diploma Deep expertise in LLM architectures, transformer models, and modern generative AI techniques. Demonstrated experience leading fine‑tuning efforts, parameter‑efficient training (e.g., LoRA/PEFT), and advanced prompt engineering. Proven ability to design and implement end‑to‑end RAG pipelines, including embedding workflows, retrieval optimization, and vector database integrations. Hands‑on experience with one or more LLM frameworks or orchestration toolchains (such as LangChain, LlamaIndex). Strong Python development skills and experience with distributed compute or GPU‑accelerated 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 Must have US citizenship or Green Card holder and must have been in the USA for 3 of the last 5 years. Preferred Requirements: Experience implementing multi‑agent or agentic AI systems for task automation and reasoning. Familiarity with LLM evaluation frameworks, structured benchmarking, or human‑in‑the‑loop refinement methods (e.g., RLHF‑style workflows). Expertise with advanced retrieval techniques such as hybrid search, graph retrieval, or long‑context optimization. Experience optimizing model inference through quantization, model compression, or model distillation. Background integrating LLM services with large‑scale analytics environments (e.g., Databricks, Snowflake, Spark). Strong skills in exploratory data analysis, feature engineering, and data modeling to support domain‑specific LLM customization. Experience developing innovative prototypes or POCs that leverage state‑of‑the‑art generative AI approaches. Exposure to emerging architectures such as mixture‑of‑experts models, long‑context transformers, or experimental generative frameworks. Target Salary Range $80,000 - $128,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. EEO EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law. #J-18808-Ljbffr Peraton