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Allen Integrated Solutions

Sensing OPIR Engineer – SME #899

AI Summary
This is a senior onsite remote-sensing engineering role supporting NGA-focused OPIR research and operational capability development in Dayton, Ohio. The engineer will lead prototype development for OPIR data-processing algorithms, troubleshoot processing pipelines, and transition advanced analytical capabilities into operational environments. The position requires deep EO/IR, signal-processing, infrared phenomenology, Python, and sensor-system expertise, along with an active TS/SCI clearance. It also involves technical documentation and collaboration with Department of Defense, Intelligence Community, industry, and research stakeholders. Candidates need at least 15 years of EO/IR algorithm-development experience and a relevant technical bachelor's degree.
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Remote from
USA
Salary
Undisclosed
Department
Software Engineering
Employment
Full Time
Experience
Senior
Published
Apply before
13 Dec 2026
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28
Application actions
2
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Opportunity details

About this role.

Remote Sensing OPIR Engineer – SME #899

Clearance Required: TS/SCI

Minimum Years’ Experience: 15 years of experience in EO/IR algorithm development

Dayton, Ohio – 100% onsite

Overall Assignment Description:

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Allen Integrated Solutions is seeking a highly skilled Subject Matter Expert in Overhead Persistent Infrared (OPIR) research engineering to support the National Geospatial-Intelligence Agency (NGA) in infrared sensing, space-based missile warning systems, data exploitation, and algorithm development. The ideal candidate will possess an extensive technical background in electro-optical/infrared (EO/IR) systems, infrared phenomenology, OPIR data analysis, and remote-sensing software development. This role requires demonstrated experience working with complex sensor systems, leading the development and testing of advanced analytical capabilities, and collaborating with government, industry, and research partners on next-generation sensing technologies.

Responsibilities

  • Lead the prototyping and development of advanced OPIR data-processing algorithms and support their transition into operational environments.
  • Evaluate and troubleshoot data-processing pipelines, identify anomalies, and coordinate remediation strategies.
  • Support the development of white papers, technical documentation, and technology-transition plans.
  • Collaborate with research organizations, Department of Defense stakeholders, Intelligence Community organizations, and external agencies.

Required Qualifications

  • Active TS/SCI clearance.
  • Bachelor’s degree in computer engineering, physics, computer science, or a related technical field.
  • At least 15 years of experience in EO/IR algorithm development.
  • Advanced understanding of EO/IR signal processing, artificial intelligence and machine learning applications, and target-system phenomenology.
  • Detailed experience with OPIR data formats and processing pipelines.
  • Advanced Python development skills.
  • Strong analytical and problem-solving skills, including the ability to diagnose sensor-performance issues, data anomalies, and software problems.

Desired Qualifications

  • Direct experience performing OPIR analysis.
  • Master’s degree in computer engineering, physics, computer science, or a related technical field.
  • Experience collaborating with NGA, NASIC, or other Intelligence Community organizations.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe role requires extensive specialized OPIR and EO/IR experience, an active TS/SCI clearance, and the ability to solve complex sensor, data, and software issues. Leading algorithm development and operational transition for intelligence-focused systems demands expert-level technical judgment.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$190,000
US market range (per year)$165k–$225k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The yearly cadence and USD market estimate are inferred from the senior, full-time US engineering scope, required TS/SCI clearance, 15+ years of specialized EO/IR experience, and Dayton, Ohio location.

Core skills

Skills and capabilities most closely associated with this opportunity.

OPIR analysisEO/IR algorithm developmentInfrared sensingSignal processingPythonRemote sensingSensor data processingData pipeline troubleshootingMachine learningArtificial intelligenceInfrared phenomenologyTechnical documentationTechnology transitionTS/SCI clearance
Sample interview questions
Describe an EO/IR or OPIR algorithm you developed and how you validated its performance.

I would explain the operational objective, input data characteristics, algorithmic approach, test datasets, performance metrics, and comparison against baseline methods. I would also describe how I addressed false alarms, missed detections, edge cases, and readiness for operational deployment.

How would you investigate an anomaly in an OPIR data-processing pipeline?

I would first establish the anomaly's scope and operational impact, then trace the pipeline from raw sensor inputs through calibration, transformations, algorithm outputs, and downstream interfaces. I would use logs, data-quality checks, controlled replay, and cross-functional reviews to isolate root cause and validate remediation.

What factors are important when applying machine learning to infrared sensing data?

Important factors include representative labeled data, sensor and environmental variability, calibration consistency, class imbalance, explainability, robustness to distribution shifts, and measurable operational performance. I would also ensure the model can be validated, monitored, and integrated safely into the larger processing pipeline.

How do you transition a research prototype into an operational analytical capability?

I would define operational requirements early, establish reproducible software and data workflows, document interfaces and assumptions, and implement verification criteria. I would then conduct performance, reliability, security, and user-acceptance testing with stakeholders before phased deployment and sustainment planning.

How do you communicate highly technical findings to Intelligence Community and Department of Defense stakeholders?

I tailor the message to the audience by leading with mission impact, confidence, limitations, and recommended actions. Supporting technical details, validation results, assumptions, and implementation risks are documented clearly so engineering and decision-making audiences can act on the findings.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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