Lead AI Security Engineer-APS

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

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