4312 Software Engineer II

OVERVIEW:

Hands-on Software Engineer II with a strong work ethic and broad technical range across full-stack development, data engineering, AI-enabled systems, networking, and visualization. Experienced in building and operating modern, open source driven applications end to end from backend APIs and data pipelines to front-end dashboards and real-time visualizations. Comfortable working across domains, learning new tools quickly, and contributing wherever needed to deliver reliable, scalable systems. Known as a "get-it-done" engineer who thrives in fast-moving, multidisciplinary environments.

REQUIRED QUALIFICATIONS:

• 5+ years of experience with a Bachelor's degree in a related technical field
• Degree may be supplemented or substituted with additional relevant years of experience
• Ability to be sponsored for a security clearance
• Core Strengths
  • Full-stack development wFith modern JavaScript/TypeScript and Python
  • Backend APIs, services, and data pipelines
  • Practical AI/ML integration (not research-heavy)
  • Real-time and batch data processing
  • Cloud-native and containerized systems
  • Strong fundamentals in networking, systems, and debugging
  • Data visualization and UI-driven insight delivery
  • Open-source tooling and pragmatic engineering
• Technical Skills
  • Programming & Frameworks
    • Languages: TypeScript, JavaScript, Python, SQL, Bash
    • Backend: Node.js, NestJS, FastAPI, Flask
    • Frontend: React, Next.js, basic D3.js, Map-based visualization libraries
    • APIs: REST, WebSockets, SSE, event-driven services
  • Data & Infrastructure
    • Databases: PostgreSQL, MySQL, MongoDB
    • Data Tools: Pandas, DuckDB, basic ETL pipelines
    • Streaming & Queues: Redis, Kafka (introductory), pub/sub concepts
    • Containers & DevOps: Docker, CI/CD basics, GitHub Actions
  • AI & Intelligent Systems
    • Practical use of LLMs , embeddings, and RAG pipelines
    • Integration of open-source models (LLaMA-family, CV, HuggingFace)
    • Experience calling and orchestrating AI services via APIs
    • Basic model evaluation, prompt design, and cost-aware usage
  • Cloud & Networking
    • Cloud Platforms: AWS / Azure (developer-level)
    • Networking fundamentals (HTTP, TCP/IP, load balancing concepts)
    • Metrics and Monitoring
  • Visualization & Geospatial (Working Knowledge)
    • Data dashboards and operational visualizations
    • Mapping libraries (Mapbox, Leaflet, Cesium - basic usage)
    • Translating raw data into usable visual insights

CLEARANCE:

• US Citizenship with eligibility to obtain a Secret clearance