RC
Software Engineer III
Reflexive Concepts
- 🇺🇸 United States
- 23 hours ago
- RAG
- Linux
- Large Language Models
- Python
- Docker
- Podman
- containerd
- Helm
- Kubernetes
- CI/CD
- GitLab CI/CD
- GitLab
- Prometheus
- Grafana
- Git
- DevSecOps
- AWS Cloud
- Atlassian
- Confluence
- Jira
- Machine Learning
- PyTorch
- TensorFlow
- Kubeflow
- SQL
- Elasticsearch
- Nim
- Triton
- vLLM
- Ray
23 hours ago
In this role, you will design, develop, deploy, and support Retrieval-Augmented Generation (RAG) solutions within a high-performance computing (HPC) Linux environment. The work spans Large Language Models, LLM orchestration frameworks, knowledge retrieval systems, embedding models, and containerized applications, delivering scalable, production-ready solutions for a mission-critical customer.
Qualifications:
- Active TS/SCI + FS Polygraph
- Master's degree in Computer Science or related discipline from an accredited college or university, plus 5 years of experience as a SWE-3, 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 7 years of experience as a SWE-3, in programs and contracts of similar scope, type, and complexity OR
- 9 years of experience as a SWE-3, in programs and contracts of similar scope, type, and complexity.
- 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 SI 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
- 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 with SQL, Elasticsearch, and Vector databases
- Knowledge of SI inferencing solutions such as Nvidia NIM/TRITON, vLLM, and direct deployment (e.g. Ray)
Software Engineer III · Reflexive Concepts