Data Engineer II at eSimplicity

Columbia, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Sep, 26

Salary

100000.0

Posted On

18 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Large Language Models, Generative AI, RAG, Python, Fine-tuning, LangChain, LlamaIndex, Vector Databases, MLOps, LLMOps, Cloud Computing, Prompt Engineering, Distributed Computing, Agentic AI, Model Quantization, Data Modeling

Industry

IT Services and IT Consulting

Description

Description About Us: eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow. Responsibilities: 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. Requirements Required Qualifications: All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation.? Bachelor’s Degree and 5+ years of previous systems engineering experience Experience developing and working with large language models (LLMs), transformer-based architectures, and generative AI solutions. Experience fine-tuning LLMs, applying parameter-efficient training methods (e.g., LoRA, PEFT), and developing effective prompt engineering strategies. Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) solutions, including embeddings, retrieval workflows, vector databases, and search optimization. Hands-on experience with LLM development frameworks and orchestration tools such as LangChain, LlamaIndex, or similar technologies. Strong Python programming skills with experience building, testing, and deploying AI/ML applications. Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference. Experience designing, deploying, and supporting AI/ML solutions in cloud environments such as Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), or similar platforms. Knowledge of MLOps and LLMOps practices, including source control, CI/CD pipelines, automated testing, monitoring, performance optimization, and model governance. Ability to lead technical discussions, collaborate effectively with cross-functional teams, mentor team members, and communicate complex technical concepts to both technical and non-technical audiences. Desired 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 (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. Working Environment: eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager. Occasional travel for training and project meetings. It is estimated to be less than 5% per year. Benefits: eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms. Reasonable Accommodation: eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources. Equal Employment Opportunity: eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any other legally protected status.

Responsibilities

Lead the design, development, and operationalization of advanced LLM capabilities and AI architecture within a cloud-based analytics ecosystem. Drive innovation in RAG, agentic frameworks, and model adaptation while ensuring robust governance and security.