Lead AI Security Engineer-APS
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 1, 2026.
Responsibilities
Consultant Software Engineer / AI Application Developer
Type: Full-Time | Level: Mid to Senior (7–10 Years of Experience)
Key Responsibilities
1. AI Application Design & Development
• Design and develop AI-powered applications using LLMs (OpenAI, Anthropic, Azure OpenAI, etc.)
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines including vector stores, chunking strategies, and embedding models
2. Agentic Solutions & Orchestration
• Develop agentic solutions using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
• Implement and integrate MCP (Model Context Protocol) servers and clients for tool-enabled LLM workflows
• Build and expose tools, APIs, and data connectors for use within agent runtimes
• Work with orchestration patterns: multi-agent systems, planning loops, memory management, and tool-use
3. Quality, Evaluation & Prompt Engineering
• Evaluate LLM output quality, implement guardrails, and optimize prompt engineering
4. Full Stack Development
• Design and develop full stack applications spanning backend (Python / .NET) and frontend (React) layers
5. Cloud & Production Deployment
• Architect and deploy solutions on cloud platforms (AWS and/or Azure)
• Collaborate with data engineers and backend teams to integrate AI capabilities into production systems
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Required Skills
Core Experience
• 7–10 years of overall software development experience
• 1–3 years of hands-on experience working in the AI/ML domain
• Strong full stack development experience: Python and/or .NET on the backend, React on the frontend
Technical Expertise
• Cloud platform experience: AWS (Bedrock, Lambda, S3, etc.) and/or Azure (Azure OpenAI, Azure ML, AKS, etc.)
• Hands-on experience building RAG pipelines (LlamaIndex, LangChain, or custom)
• Experience with vector databases (Chroma, Qdrant, Weaviate, pgvector, etc.)
• Familiarity with MCP and tool/function calling patterns in LLM applications
• Experience designing agentic workflows (ReAct, plan-and-execute, multi-agent)
• REST API development (FastAPI / Flask / ASP.NET)
• Understanding of prompt engineering, context window management, and LLM evaluation
________________________________________
Nice to Have
• Familiarity with observability tools for LLM apps (LangSmith, Arize, Helicone)
• Knowledge of fine-tuning or RLHF workflows
• Exposure to MCP server development (SSE / stdio transport)
• Containerization with Docker / Kubernetes
• Experience working in the cyber domain or having cyber knowledge will be an added advantage
Profile required
Required Skills
Core Experience
• 7–10 years of overall software development experience
• 1–3 years of hands-on experience working in the AI/ML domain
• Strong full stack development experience: Python and/or .NET on the backend, React on the frontend
Technical Expertise
• Cloud platform experience: AWS (Bedrock, Lambda, S3, etc.) and/or Azure (Azure OpenAI, Azure ML, AKS, etc.)
• Hands-on experience building RAG pipelines (LlamaIndex, LangChain, or custom)
• Experience with vector databases (Chroma, Qdrant, Weaviate, pgvector, etc.)
• Familiarity with MCP and tool/function calling patterns in LLM applications
• Experience designing agentic workflows (ReAct, plan-and-execute, multi-agent)
• REST API development (FastAPI / Flask / ASP.NET)
• Understanding of prompt engineering, context window management, and LLM evaluation
________________________________________
Nice to Have
• Familiarity with observability tools for LLM apps (LangSmith, Arize, Helicone)
• Knowledge of fine-tuning or RLHF workflows
• Exposure to MCP server development (SSE / stdio transport)
• Containerization with Docker / Kubernetes
• Experience working in the cyber domain or having cyber knowledge will be an added advantage