Software Engineer 4

Principal Software Engineer (SWE4) –

Wyetech is seeking a motivated Principal Software Engineer (SWE4) / Full-Stack Developer to support the Tradecraft Evolution mission. The successful candidate will work closely with mission stakeholders to capture requirements and design, develop, deploy, and sustain a production-ready Business Intelligence (BI), data warehousing, and advanced analytics environment.

This position requires expertise in full-stack software development, cloud computing, data engineering, business intelligence, and AI/ML operations. The Software Engineer will leverage Python, Java, R, and AWS cloud technologies to develop scalable enterprise analytics solutions, integrate diverse data sources, and deliver mission-critical capabilities that support intelligence analysis, operational decision-making, and technology discovery.

Required Skills/Experience:

• Strong proficiency in object-oriented programming and software development using Python, Java, and R.

• Extensive experience designing, developing, deploying, and sustaining full-stack software applications and enterprise analytics solutions.

• Experience with AWS cloud computing, including provisioning, configuring, and managing AWS resources.

• Experience designing and implementing enterprise data warehousing solutions.

• Experience developing and integrating Business Intelligence solutions using Tableau and Power BI.

• Experience creating enterprise dashboards, analytics products, and reporting capabilities.

• Experience with data engineering, data integration, and advanced analytics.

• Experience developing APIs and integrating disparate data sources to support business intelligence and mission analytics.

• Experience with Jupyter Notebooks for data analysis, development, and experimentation.

• Experience with AI/ML operations (MLOps), including deploying and operationalizing machine learning models.

• Experience with Docker containerization and Kubernetes orchestration.

• Experience developing and maintaining automated end-to-end data processing and machine learning pipelines.

• Experience with Large Language Models (LLMs), including prompt engineering and performance optimization.

• Ability to collaborate directly with mission stakeholders to gather requirements and translate operational needs into technical solutions.

• Experience supporting the full software development life cycle, including requirements analysis, design, implementation, testing, integration, deployment, and maintenance.

Desired Technical Skills:

• Knowledge of SIGINT architectures and intelligence mission environments.

• Experience with Apache NiFi dataflows and data integration.

• Familiarity with customer corporate tools, systems, and data repositories.

• Experience supporting advanced analytics, analytic watermarking, and sandbox environments.

• Experience developing and implementing pilot initiatives and emerging technology solutions.

• Experience integrating AI/ML capabilities into enterprise business intelligence and analytics environments.

• Experience optimizing cloud-based applications for scalability, security, reliability, and operational efficiency.

• Demonstrated technical leadership and experience mentoring or guiding software development teams.

Capabilities:

• Design, develop, implement, test, deploy, and maintain complex software systems and enterprise applications.

• Apply computer science principles, algorithms, discrete mathematics, probability, and statistics to software engineering challenges.

• Analyze mission and user requirements to develop scalable, secure, and maintainable software solutions.

• Design and implement full-stack applications that integrate backend services, APIs, databases, and user-facing analytics tools.

• Develop and sustain enterprise Business Intelligence and data warehousing environments.

• Provision, configure, and integrate AWS cloud resources to support software development and analytics operations.

• Develop and integrate Tableau and Power BI dashboards to support mission reporting and operational decision-making.

• Create APIs and analytical capabilities that leverage disparate data sources to address knowledge gaps in user activities, collection efforts, and technology discovery.

• Design and implement data processing, transformation, and integration workflows.

• Support advanced analytics, analytic watermarking, sandbox environments, and pilot initiatives.

• Develop and operationalize AI/ML models using MLOps methodologies and automated deployment pipelines.

• Implement Docker containerization and Kubernetes orchestration to support scalable AI/ML applications.

• Optimize Large Language Model performance through advanced prompt engineering and integration with enterprise analytics solutions.

• Collaborate with mission stakeholders, data engineers, analysts, and technical teams to define requirements and deliver production-ready capabilities.

• Evaluate software designs and implementations to ensure functionality, reliability, security, and maintainability.

• Develop technical documentation, training materials, and software engineering artifacts.

• Present technical briefings, demonstrations, and solution recommendations to stakeholders.

• Provide technical guidance and leadership throughout the software development life cycle.

Qualifications:

Candidates must meet one (1) of the following education and experience combinations:

• Bachelor's Degree in Computer Science or a qualifying related field and a minimum of eleven (11) years of relevant experience.

• Master's Degree in Computer Science or a qualifying related field and a minimum of nine (9) years of relevant experience.

• Doctoral Degree in Computer Science or a qualifying related field and a minimum of seven (7) years of relevant experience.

• Associate's Degree and a minimum of thirteen (13) years of relevant experience may be considered for candidates with substantial, directly related experience.

Degree Requirements:

A degree in Computer Science is preferred. Related degrees, including Engineering or Mathematics, may be considered if the academic program includes a concentration of coursework in the following foundational Computer Science areas:

• Algorithms

• Computer architecture (excluding network architecture)

• Programming methodologies and languages

• Data structures