Software Engineer 3 (IDN - 202)

Serving Maryland and the Greater Washington D.C. area, SageCor Solutions (SageCor) is a growing company bringing complete engineering services and true full lifecycle System Engineering services to areas requiring (or desiring) nationally-recognized expertise in high performance computing, large data analytics and cutting edge information technologies. Active TS/SCI w/ Polygraph required.

SWE-3 Qualifications:

Master’s degree in computer science or related discipline from an accredited college or university, plus five (5) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity. OR Bachelor’s degree in computer science or related discipline from an accredited college or university, plus seven (7) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity OR Nine (9) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity.

Position Description:

The Software Engineer shall design, develop, deploy, and support Retrieval-Augmented Generation (RAG) solutions within a high-performance computing (HPC) Linux environment. The successful candidate will have hands-on experience with Large Language Models (LLMs), LLM orchestration frameworks, knowledge retrieval systems, embedding models, and containerized applications. Candidates must be proficient in Python, Kubernetes, Helm, CI/CD automation, and secure AI system development, with the ability to deliver scalable, production- ready SI solutions in mission-critical environments.

Position Required Skills:

• Proven experience working in Linux environments, including advanced use of the Linux command-line interface (CLI) for development, troubleshooting, and system administration
• Recent hands-on software development experience using Python, with a strong understanding of modern software engineering practices and frameworks
• Experience with containerization technologies, such as Docker, Podman, and containerd, for application packaging, deployment, and lifecycle management
• Experience designing, authoring, and deploying Helm charts to manage Kubernetes-based applications and services
• Experience developing, testing, deploying, and supporting containerized applications in production environments.
• Experience creating, configuring, and managing Kubernetes resources, including Deployments, Services, ConfigMaps, Secrets, Ingresses, and Operators
• Working knowledge of Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, embedding models, and vector databases
• Experience implementing and maintaining CI/CD pipelines using tools such as GitLab CI/CD, Flux CD, GitLab Runners or similar tools
• Experience leveraging observability, metrics, logging, and monitoring solutions including Prometheus and Grafana
• Proficiency with Git-based source control workflows, including branching strategies, code reviews, pull/merge requests, and collaborative development practices
• Understanding of software development lifecycle (SDLC) best practices, including automated testing, security scanning, code quality analysis, and DevSecOps principles

Position Desired Skills:

• Familiar with developing, deploying, troubleshooting, and sustaining mission applications in an AWS Cloud environment
• Experience with the Atlassian suite of tools including Confluence and Jira
• Experience working with, and debugging, GPU-enabled applications
• Experience using a machine-learning framework (PyTorch, TensorFlow, etc)
• Experience with other ML pipelines/frameworks like KubeFlow, NeMo, PyTorch Lightning, etc.
• Experience working with and debugging GPU-enabled applications -Experience with SQL, Elasticsearch, and Vector databases
• Knowledge of SI inferencing solutions such as Nvidia NIM/TRITON, vLLM, and direct deployment (e.g. Ray) Consistent with federal and state law where SageCor conducts business, SageCor Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.