Job#: 3046696 Job Description: Generative AI Architect
Location: Home, Maryland
Role Overview
The LLM Specialist will drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. This role leads 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. The specialist will 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. 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. This role requires that all candidates are eligible to obtain & maintain a Public Trust clearance.
Key Responsibilities
- Lead fine-tuning efforts, parameter-efficient training (e.g., LoRA/PEFT), and advanced prompt engineering.
- Design and implement end-to-end RAG pipelines, including embedding workflows, retrieval optimization, and vector database integrations.
- Architect and deploy AI/ML or LLM workflows within cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Lead technical discussions, mentor team members, and communicate complex AI concepts to diverse audiences.
Required Qualifications
Education: A bachelor's degree in computer science, software engineering or a relevant field is required.
Experience: 5-7 years of experience is required. Must be eligible to obtain & maintain a Public Trust clearance.
Technical Skills:- Deep expertise in LLM architectures, transformer models, and modern generative AI techniques.
- 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.
- Solid understanding of MLOps/LLMOps practices, including versioning, CI/CD, automated testing, monitoring, and model governance.
Preferred Qualifications
- 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.
- 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.
- Active or prior Public Trust level clearance or higher.
Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico.
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