Mid-Level Project/Product Lead (Systems Architect)

As a Mid-Level Project/Product Lead (Systems Architect) at Redhorse Corporation, your primary responsibilities include analyzing software development requirements, designing scalable architectures for tools within the Advana platform, and collaborating with a hybrid team of professionals. You'll ensure that technical requirements align with business goals and develop user-friendly search tools that make a significant impact on data-driven decision-making within the DoD.

To qualify for the Mid-Level Project/Product Lead (Systems Architect) role at Redhorse Corporation, candidates should have a Bachelor’s degree with 5-7 years of related experience, or a Master’s degree with 3 years of experience. Key qualifications include proficiency in scripting languages like Python or R, knowledge of big data programming languages, experience with Elasticsearch, and an active Top Secret security clearance with SCI eligibility.

Collaboration is key for a Mid-Level Project/Product Lead (Systems Architect) at Redhorse Corporation. You'll work closely with analysts, engineers, data scientists, UX designers, and developers to build and deploy robust search and analytical tools. By fostering open communication and teamwork, you will help ensure that the systems designed meet both technical and user requirements effectively.

In the Mid-Level Project/Product Lead (Systems Architect) role at Redhorse Corporation, you will work with cutting-edge technologies, including AI/ML techniques, NLP, big data programming languages like Java and Scala, and cloud-based environments such as AWS and GovCloud. Your experience with tools like Neo4j for Knowledge Graph construction will also be beneficial in enhancing our products.

Knowledge of compliance is crucial for the Mid-Level Project/Product Lead (Systems Architect) role at Redhorse Corporation. Familiarity with cybersecurity compliance and secure software development methodologies will help you navigate the process for obtaining Authority to Operate (ATO) on defense and intelligence networks, ensuring that the systems you develop meet essential security standards.

When analyzing software development requirements, I focus on understanding the business objectives first. I conduct thorough research and engagement with stakeholders to ensure their needs are addressed while also considering cost-effective solutions and optimal design architectures that can handle complex queries across large datasets.

In my previous roles, I have extensively utilized scripting languages like Python for data analysis and automation. This experience has allowed me to develop efficient algorithms and solutions that drive project success. I understand the nuances of integrating these scripts effectively within the broader system architecture.

In a recent project, I led a cross-functional team to develop a data processing tool. My role involved coordinating with data scientists and UX designers to ensure that both technical and user needs were met. I facilitated regular meetings and feedback loops to create a seamless development process, resulting in a successful tool deployment.

To optimize software designs, I focus on profiling the execution of the software, identifying bottlenecks, and making architectural enhancements. Implementing performance metrics and optimizing algorithms can lead to significant improvements, ensuring that the final system meets the desired performance targets.

I have hands-on experience configuring and using Elasticsearch to create scalable, fast search capabilities within system architectures. This involvement has provided me with insights into index management, query optimization, and integrating Elasticsearch effectively within broader data processing frameworks.

The most challenging aspect of designing scalable architectures is balancing performance with complexity. It's essential to create a solution that can grow and handle increasing loads without sacrificing maintainability. I address this by carefully evaluating design patterns and implementing modular components that allow for easy scaling.

I have a solid understanding of natural language processing techniques, having worked on projects that involved sentiment analysis and text classification. This experience allows me to contribute effectively to designs that utilize NLP for enhancing user interaction and extracting meaningful insights from unstructured text data.

Ensuring adherence to DoD standards involves staying updated on current guidelines and implementing best practices throughout the project lifecycle. I engage in regular training and review sessions with my peers to ensure that all security, compliance, and technical requirements are met consistently.

I have substantial experience with cloud-based environments like AWS and GovCloud, where I have deployed solutions for various data processing tasks. Understanding cloud services and their security implications has allowed me to design architectures that leverage the scalability and robustness of cloud environments effectively.

My approach to machine learning model development involves understanding the problem domain first, followed by data preprocessing and feature engineering. I advocate for an iterative process that includes model training, validation, and optimization, focusing on ensuring that the model can be effectively integrated and productized within the overall system architecture.