Senior Software Developer

Parsons Corporation•USA VA (Virtual Office), VA

8d•$125,100 - $225,200

About The Position

Parsons is seeking a Senior Software Developer to support DTRA's Data Lake (AIDA-TAC) or other AI/ML and data engineering initiatives. The role involves building and maintaining scalable data pipelines and cloud-based data architectures, developing AI/ML-enabled tools, and implementing data quality workflows. The developer will collaborate across teams on analytics, machine learning, and knowledge graph construction while applying data security practices aligned with DoD and NIST standards. The position is part of Parsons' Federal Solutions team, which provides services and solutions to U.S. government customers.

Requirements

Bachelor’s degree or higher in Computer Science, Data Engineering, Data Science, Software Engineering, Information Systems, or a related technical field.
8+ years of experience in data engineering, software development, or ETL development in cloud or enterprise environments.
Proficiency in Python, Java, C++, SQL, and Spark, with hands-on experience in AI/ML frameworks such as PyTorch or TensorFlow.
Hands-on experience with AWS or Azure and cloud-native data services.
Experience with containerization using Docker and Kubernetes, and DevOps practices including CI/CD and automated testing.
Strong understanding of data modeling, data partitioning, and data architecture best practices.
Familiarity with data security, encryption, and access control mechanisms.
An active Secret or higher security clearance.

Nice To Haves

Proficiency with OCR and document text-extraction technologies.
Experience with document layout analysis, including detection of paragraphs, tables, figures, captions, headers, footers, and annotations.
Familiarity with chart understanding and plot digitization, including extraction of axes, labels, legends, data points, trends, units, and error bars.
Familiarity with Optical Chemical Structure Recognition (OCSR) for converting molecular depictions into machine-readable formats such as SMILES, InChI, or molecular graphs.
Ability to associate extracted data with its source document, page, figure, table, caption, and bounding box.
Familiarity with confidence scoring, validation, error correction, and human-in-the-loop review workflows.
Experience designing normalized schemas or knowledge graphs for scientific and chemical data.
Experience developing and deploying AI/ML models and integrating them into production data pipelines.
Experience with DoD cybersecurity and data governance standards such as NIST SP 800-171, STIG, and RMF.
Experience with metadata management, data cataloging, and data quality assessment tools.
Familiarity with advanced search and indexing technologies such as vector/semantic search and LLMs.
Experience with modern database platforms such as Postgres, MongoDB, MySQL, or Neo4j.

Responsibilities

Design, develop, and maintain scalable data pipelines and ETL processes for ingesting and transforming large volumes of chemical and biological threat data.
Build and optimize cloud-based data architectures, integrating with data lakes and external systems via APIs.
Develop, deploy, and support AI/ML-enabled tools for data mining, predictive modeling, and knowledge discovery.
Implement and automate data quality, validation, and enrichment workflows, including generation of data quality reports.
Collaborate with cross-functional teams to support analytics, machine learning, and knowledge graph construction.
Apply data security, encryption, and access control strategies in compliance with DoD and NIST standards.
Participate in Agile sprints and contribute to technical documentation and continuous improvement of data and software solutions.