AI Software Engineer

Blu Omega is a Woman-Owned Small Business delivering technology and cybersecurity solutions to federal agencies. They are seeking an Agentic AI & LLM Platforms Engineer to support the GRACE AI platform, focusing on building and maintaining backend infrastructure and agentic AI systems.

Responsibilities:

• Implement and iterate on agentic workflows, including tool-calling, multi-step reasoning, planning, memory, and agent-to-agent communication patterns
• Build and maintain MCP (Model Context Protocol) client-side integrations for tool discovery and invocation
• Develop tool definitions, input/output schemas, error handling, retry logic, and result formatting for the tool library
• Contribute to multi-agent orchestration patterns that are reliable and debuggable in production
• Implement LLM orchestration logic, including prompt construction, context management, model selection, and response parsing across OpenAI GPT, Anthropic Claude, and Google Gemini
• Build and maintain RAG pipeline components such as query formulation, result ranking, citation grounding, and hallucination mitigation
• Develop prompt engineering patterns and system prompts to ensure quality and consistency across models
• Manage context window budgets through truncation, summarization, and pagination logic
• Build LLM evaluation components for grounding, regression testing, safety, and quality metrics
• Write prompts and pipelines considering token economics and cost constraints
• Build secure, well-tested backend features, including API integrations with internal and external data sources and APIs
• Contribute to monitoring, logging, distributed tracing, and fallback patterns for AI service dependencies
• Work within Azure infrastructure, including Azure Functions, Azure API Management, Azure Container Apps, and Azure OpenAI Service
• Support CI/CD pipelines, deployment automation, and infrastructure as code

Requirements:

• Bachelor's or Master's in Computer Science, Software Engineering, or related field, or equivalent practical experience
• 3+ years of professional software engineering experience building and operating production systems
• Proven experience in high-velocity environments shipping complex products end-to-end
• Strong proficiency in Python and at least one other backend language
• Familiarity with modern backend frameworks and async patterns
• Solid understanding of algorithms, data structures, APIs, and software design patterns
• Experience with cloud platforms (Azure, AWS, or GCP)
• Experience with containerization and CI/CD pipelines