Description
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)
