Senior Full-Stack Engineer
General Information
Requisition # 692
Locations USA-VA-Arlington
Posting Date 05/01/2026
Security Clearance Required - Active Public Trust
Remote Type Hybrid
Time Type Full time
Description & Requirements
Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Senior Full-Stack Engineer to join our team in Arlington, VA who will help lead development of the analytics platform. This is a high-ownership role: you'll drive front-end architecture decisions, contribute meaningfully to Python backend services, mentor engineers on the team, and ship complex features end-to-end.
The balance between front-end and back-end work in this role evolves with the product—some sprints emphasize UI development, while others focus on Python-based pipelines and document-processing services. We’re seeking a true full-stack engineer who is equally comfortable operating across both layers and can adapt as priorities shift, rather than someone with a strong bias toward one side of the stack.
As a Sr. Full-Stack Engineer, you will lead front-end architecture for a growing internal platform, driving component design, state management, routing, and performance optimization, while also contributing to Python backends that power document processing, OCR, summarization, and inference pipelines. You will build end-to-end large-scale PDF upload workflows with chunking, resumability, progress feedback, and robust error handling, supported by scalable Python services, and develop interactive prompt-guidance and conversation continuity features, including context upload and deep integration with OCR and inference systems.
Responsibilities include but are not limited to:
- Build and maintain strongly typed front-end components using TypeScript and React, including complex document and conversation workflows integrated with Python services
- Develop advanced file upload interfaces with chunking, resumable flows, progress tracking, and resilient error handling
- Leverage browser APIs (File API, Streams, Web Workers) and optimize front-end performance
- Lead front-end architecture decisions, design reviews, and establish component standards
- Develop and extend Python backend utilities for document processing, chat/inference, OCR, and pipeline orchestration
- Write Python scripts for QA automation, data validation, CI/CD, and support serverless/containerized workflows
- Mentor engineers, lead technical discussions, and produce clear internal documentation
- Ensure accessibility (WCAG 2.1 / Section 508), testing coverage, and strong GitHub/CI/CD governance practices
Minimum Qualifications:
- Expert-level TypeScript and React, with a track record of owning complex front-end systems end-to-end
- Strong, production-grade Python skills: not just scripting, but building and maintaining backend utilities, integrating with microservices, and contributing to data and inference pipelines
- Comfort moving fluidly between front-end and backend work sprint-to-sprint without a strong preference for either
- Proven delivery of large-file upload systems (chunking, resumable uploads, error recovery)
- Hands-on experience with browser APIs (File API, Streams, Web Workers) and front-end performance profiling
- Experience mentoring engineers and leading technical design discussions
- Strong Git/GitHub fluency and CI/CD experience
- Demonstrated accessibility experience — hands-on work with WCAG or Section 508 compliance
Preferred Qualifications:
- Experience building analytics or AI-assisted internal tooling
- Familiarity with OCR and document-processing systems
- Experience with serverless architectures (Lambda, S3-based pipelines)
- Experience in regulated or security-conscious development environments
- Comfort working in cross-disciplinary teams alongside data scientists and cloud engineers
Clearance Requirements:
- Must have a current/active Public Trust at time of hire.
About Elder Research, Inc - People Centered. Data Driven
Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.
If you need a reasonable accommodation to apply for a position with Elder Research, please email us at [email protected] and provide your name and contact information.
What We Do
Elder Research is a recognized leader in data science, machine learning, and artificial intelligence consulting. Founded in 1995 by Dr. John Elder, Elder Research has helped government agencies and Fortune Global 500® companies solve real-world problems in diverse industry segments. Our goal is to transform data, domain knowledge, and algorithmic innovations into world-class analytic solutions. When we combine the business domain expertise of our clients with our deep understanding of advanced analytics, we create a team that can extract actionable value from the data. Our areas of expertise include data science, text mining, data visualization, scientific software engineering, and technical teaching. Experience with diverse projects and algorithms, advanced validation techniques, and innovative model combination methods (ensembles) enables Elder Research to maximize project success for a continued return on analytics investment. In 2020 we acquired the Institute for Statistics Education at Statistics.com to provide focused data science, analytics, and statistics training for corporations and individuals. The Institute’s certificates and degrees are certified by the State Council of Higher Education for Virginia, and its courses are approved by the American Council on Education. Elder Research’s Analytics Services are designed to scale based on the unique requirements of each organization and can maximize the client’s return on analytic investment. Elder Research is also a leader in advanced analytic training and offers a variety of training services directed at each of the key stakeholders within an organization. Training builds a common foundation and vision for analytics across business units and lead to the successful adoption, deployment, and maintenance of analytic models within an organization.
