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Automation Engineering Manager Jobs in Springfield, VA

Bowhead

Lead Automation Engineer

Arlington, VA · On-site

$117K - $154K/yr

Responsibilities Automation Engineering & Leadership: Serve as the lead technical engineer for the ... Manage and provision cloud infrastructure on AWS using Infrastructure as Code (IaC) tools ...

Exiger

Engineering Manager

Mclean, VA · On-site

Experience with CI/CD, deployment automation, release management, observability, and operational ... Proven ability to mentor engineers, build ownership, manage delivery, and foster a strong ...

Second Front Systems

Engineering Manager

Washington, DC · Remote

$190K - $230K/yr

ABOUT THE ROLE Second Front Systems (2F) is seeking an ambitious and visionary Engineering Manager ... and automation frameworks. * Demonstrated success leading cross-functional initiatives in ...

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All JobsAutomation Engineering Manager JobsAutomation Engineering Manager Jobs in Springfield, VA

Automation Engineering Manager information

See Springfield, VA salary details

$94K

$144.2K

$181.2K

How much do automation engineering manager jobs pay per year?

As of Jun 19, 2026, the average yearly pay for automation engineering manager in Springfield, VA is $144,199.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,700.00 and $167,100.00 per year, depending on experience, location, and employer.

What does an Automation Engineering Manager do?

An Automation Engineering Manager oversees the design, implementation, and optimization of automated systems in manufacturing or software development. They lead a team of engineers to improve efficiency, reduce costs, and enhance productivity through automation technologies. Responsibilities include project management, system integration, troubleshooting, and ensuring compliance with industry standards. They collaborate with other departments to align automation strategies with company goals. Strong technical expertise, leadership skills, and problem-solving abilities are essential for this role.

What are the key skills and qualifications needed to thrive in the Automation Engineering Manager position, and why are they important?

An Automation Engineering Manager should have a strong background in automation technologies, process improvement, project management, and a relevant engineering degree. Familiarity with PLC/SCADA systems, robotics, industrial control systems, and certifications such as PMP or Six Sigma is often required. Excellent leadership, problem-solving, and communication skills help drive team performance and foster cross-functional collaboration. These capabilities are essential for delivering efficient automation solutions, ensuring project success, and guiding multidisciplinary teams in fast-paced environments.

What are some typical challenges faced by Automation Engineering Managers in their day-to-day work?

Automation Engineering Managers often balance multiple projects and deadlines while ensuring high quality and compliance with industry standards. A common challenge is integrating new automation technologies with existing systems, which requires careful planning and troubleshooting. Collaboration with cross-functional teams—including operations, IT, and maintenance—is crucial for aligning technical solutions with business goals. Additionally, staying current with emerging automation trends and training team members on new tools is a key part of the role, helping drive continuous improvement and operational efficiency.

What job categories do people searching Automation Engineering Manager jobs in Springfield, VA look for? The top searched job categories for Automation Engineering Manager jobs in Springfield, VA are:
What cities near Springfield, VA are hiring for Automation Engineering Manager jobs? Cities near Springfield, VA with the most Automation Engineering Manager job openings:
Automation Engineering Manager jobs near you
Infographic showing various Automation Engineering Manager job openings in Springfield, VA as of June 2026, with employment types broken down into 70% Full Time, and 30% Part Time. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $144,199 per year, or $69.3 per hour.

AI Security Automation Engineering - Lead

Kanor Systems

Bethesda, MD • On-site, Remote

Other

Posted 21 days ago

Job description

Role Level

Lead/Manager- AI Security Automation Engineering

Role Type

Individual Contributor

Location

Remote-friendly / Marriott HQ

Core Stack

Python Go Neo4j LLM APIs Graph Databases

Frameworks

NIST AI RMF OWASP LLM Top 10 ISO 42001 OSCAL

Responsibilities:

  • Design review templates ("archetypes") for every major AI deployment pattern: agentic AI, conversational platforms, IoT+AI, contact center AI, and enterprise SaaS.
  • Build intake questionnaires that auto-route submissions to the right control checklists based on deployment model (SaaS, on-prem, hybrid, multi-cloud, API-integrated).
  • Define complexity weighting models and set measurable cycle-time targets per review type.
  • Build LLM-powered tools that auto-draft threat models from architecture descriptions, map controls to findings, and surface cross-review risk patterns.
  • Develop automated intake and triage pipelines - intent classification, complexity scoring, archetype detection, priority assignment - integrated with ServiceNow or Jira.
  • Own the operational dashboards: cycle time, queue depth, completion rate, rework rate.
  • Design and maintain a labeled property graph ontology connecting AI patterns, controls, threats, standards, deployment paradigms, and risk tiers.
  • Implement graph traversal queries for gap analysis (risk dimension unaddressed controls), tier compliance, and cross-pattern coverage.
  • Export graph data to support executive reporting and audit evidence packages.
  • Build control mapping pipelines that link review findings to AI risk dimensions and OSCAL-aligned compliance attestations.
  • Drive alignment with EU AI Act obligations: risk classification, quality management traceability, and risk management documentation.
  • Coordinate with assurance and risk teams on scoring handoff criteria and independent verification.

Must-Have Experience

  • 10+ years building and operating complex data models, knowledge graphs, or system architectures - especially in compliance, policy, or regulatory domains.
  • 2+ years in cybersecurity: security assessments, threat modeling, control mapping, or risk analysis in enterprise or regulated environments.
  • Proven track record converting manual review processes into repeatable, metrics-driven, AI-assisted operations.
  • Experience building AI/ML automation for security, compliance, or GRC workflows - not just using tools, but engineering them.
  • Production-grade delivery: automation systems running at enterprise scale, not proof-of-concept only.
  • Strong executive communication: able to present pipeline metrics upward and threat models to architecture review boards.

Technical Skills

  • Python and Go for building automation tooling, API integrations, and data pipelines.
  • Graph databases: Neo4j, KuzuDB, NetworkX, openCypher, or GraphML - including ontology design and graph-based reasoning.
  • LLM and agent frameworks: PydanticAI, LangChain, or equivalent; experience with Claude (Bedrock), Azure OpenAI, or similar foundation model APIs.
  • AI system architecture depth: LLMs, RAG pipelines, MCP, vector stores, agent orchestration.
  • Security frameworks: NIST AI RMF, ISO 42001, NIST CSF, OWASP LLM Top 10, OWASP Agentic Top 10, MITRE ATLAS, OSCAL.
  • Workflow platform APIs: ServiceNow, Jira, or equivalent for end-to-end process automation.

Education

  • Master's or Ph.D. in Computer Science, Cybersecurity, Information Systems, or related STEM field - or equivalent experience demonstrated in role.

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