SOFTWARE DEVELOPER/ENGINEER (CYBER)

Job Responsibilities

• Design, develop, and maintain RAG pipelines integrating vector databases, embeddings, and LLMs for accurate, context-aware inference.
• Implement and optimize retrieval logic, prompt engineering, and post-processing of LLM outputs.
• Build and integrate backend services using .NET/C#, Go, and/or Python.
• Collaborate with AI/ML engineers, data scientists, and stakeholders to translate requirements into production-grade features.
• Ensure application security, performance, scalability, and compliance with government standards.
• Troubleshoot and optimize AI-assisted workflows, including latency, accuracy, and cost considerations.
• Participate in code reviews, testing, and documentation in an Agile environment.

Required Skills & Qualifications

• Active TS or ability to obtain TS/SCI clearance.
• At least 3+ years of professional software development experience.
• Strong experience in at least two of the following: .NET/C#, Go (Golang), Python.
• Solid understanding of all languages listed is a plus.
• Familiarity at the developer level with AI/ML fundamentals, including embeddings and vector searching, RAG patterns, LLM inference (prompting, context windows, token management), and basic evaluation metrics for generative AI.
• Experience building RESTful APIs, microservices, or backend systems.
• Experience with non-frontier (open) AI models running in local or self-hosted environments.

Desired Skills & Qualifications

• Direct experience developing and deploying AI-assisted applications (chatbots, knowledge assistants, document intelligence tools).
• Hands-on work with RAG frameworks/tools such as LangChain, LlamaIndex or similar.
• Experience implementing vector databases such as Pinecone, Weaviate, Chroma, pgvector, etc.
• Familiarity with Python data/AI ecosystem (NumPy, Pandas, Hugging Face, sentence-transformers).
• Experience with .NET integrations with AI services or Go-based backend services for high-performance AI workloads.
• Experience developing in secure/controlled environments (FedRAMP, gov-cloud, air-gapped enclaves).
• Knowledge of MLOps basics (model versioning, monitoring, CI/CD for AI).