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 Lang Chain, Lang Graph, Auto Gen, 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 (Llama Index, Lang Chain, 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 (Lang Smith, 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

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