Generative AI Architect

Location: Home, Maryland

About the Role

The Generative AI Architect 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. All candidates must be eligible to obtain and maintain a Public Trust clearance.

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 GCP.
• Lead technical discussions, mentor team members, and communicate complex AI concepts to diverse audiences.

Requirements

• Bachelor's degree in computer science, software engineering, or a relevant field.
• 5-7 years of experience in a related role.
• Eligibility to obtain and maintain a Public Trust clearance.

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.

Benefits

• Medical, dental, vision, life, and disability insurance plans.
• Employee Stock Purchase Program (ESPP).
• 401K program with company match after 12 months of tenure.
• Health Savings Account (HSA) on the HDHP plan.
• SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions.
• Corporate discount savings program and other discounts.
• On-demand training program, access to certification prep, and a library of technical and leadership courses/books/seminars after 6+ months of tenure.
• Certification discounts and perks for associations including CompTIA and IIBA.
• Dedicated customer service team for benefits and resources, and a certified Career Coach.