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Software Development Manager; AI​/ML Security Clearance

Job in Herndon, Fairfax County, Virginia, 20170, USA
Listing for: Anonymous Employer
Full Time position
Listed on 2026-06-07
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Engineer
Job Description & How to Apply Below
Position: Software Development Manager (AI/ML) with Security Clearance
We are seeking an expert Software Development Manager / Lead Engineer to spearhead the evolution of an enterprise-wide, data-centric mission management platform. Operating at the intersection of big data, distributed systems, and advanced analytics, you will lead a talented, multi-disciplinary team of Software Developers, ETL Engineers, and Data Scientists. This is a hands-on technical leadership role for an elite engineer who thrives on building scalable architecture from the ground up.

You will own the design and implementation of high-performance, distributed web services capable of processing petabyte-scale structured and unstructured data. Your mission is to integrate production-grade Artificial Intelligence and Machine Learning (AI/ML) capabilities into workflows that enable mission users to rapidly access, extract, and exploit critical information.

Key Responsibilities

• AI/ML Integration:
Drive the seamless integration of state-of-the-art AI/ML models and data science capabilities into a high-availability production environment.

• Architecture & Scalability:
Architect, optimize, and enhance microservices-based platforms, ensuring extreme performance, robust security posture, and seamless handling of massive raw data ingest pipelines.

• Hands-on Development & Prototyping:
Design, write, and unit-test high-quality code. Build rapid, high-fidelity prototypes to solidify functional requirements and drive technical strategy.

• Technical Leadership & Stakeholder Management:
Deconstruct complex technical concepts into discrete development tasks, lead iterative Agile sprints (Scrum/Kanban), and deliver high-impact demonstrations to both technical and non-technical stakeholders.

• Documentation & Governance:
Champion the creation of comprehensive technical documentation, application workflow blueprints, and compliance procedures to support program milestones and control gates. Required Experience & Technical

Skills:

• Polyglot Backend Expertise: 4–6 years of deep backend proficiency splitting production environments between Python (preferred language) and Java utilizing Object-Oriented Design patterns.

• Modern Frontend Systems: 4–6 years of hands-on experience building sleek, scalable user interfaces using Angular.

• Cloud Architecture &

Infrastructure: 6–8 years of expertise designing and deploying secure, enterprise-level architectures within Amazon Web Services (AWS) or equivalent secure government cloud environments.

• Enterprise Search & Analytics: 6–8 years working heavily with massive search engine frameworks such as Elasticsearch, Open Search, or Solr/Lucene.

• Databases & Containers: 6–8 years managing a diverse database landscape across both SQL and No

SQL paradigms, paired with deep containerization experience using Docker or Podman.

• Advanced Linux Engineering: 6–8 years of intensive Linux system administration experience, including shell scripting, drive mounting, environment configuration, and memory/process performance diagnostic diagnostics.

• Data Pipelines & AI Foundations: 2–3 years of direct exposure to data science concepts, machine learning development workflows, and 2–4 years of heavy ETL pipeline engineering with massive, messy data sets.

• Agile Workflows:
Proven experience leading development sprints using Jira, Confluence, and Git Hub/Git Lab. Highly Desired (Bonus)

Skills:

• Advanced text analytics implementations (e.g., entity extraction, sentiment analysis, document summarization, and categorization).

• Experience evaluating state-of-the-art ML algorithms and building out ML-focused Proof of Concepts.

• Exposure to industry-standard ML and Natural Language Processing (NLP) frameworks like PyTorch, Tensor Flow, Keras, spaCy, or NLTK.

• Familiarity with advanced data disciplines like Optical Character Recognition (OCR), Named Entity Recognition (NER), BERT models, image recognition, or fuzzy search indexing.

• Experience utilizing data visualization toolsets (e.g., Pandas, Tableau, D3.js).
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