This is an excellent opportunity for someone early in their career to grow into advanced AI engineering, agentic architectures, and enterprise-scale AI delivery.

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  Assist in designing, developing, and testing AI agents, GenAI workflows, and LLM-powered solutions.

• Support implementation of retrieval-augmented workflows (RAG) including embeddings, vector databases, and context engineering.

• Develop Python-based backend components, APIs, and integration logic for AI-driven systems.

• Collaborate with senior AI engineers to build multi-agent workflows, tool integrations, and agent orchestration pipelines.

• Contribute to development within AI platforms, Azure AI Foundry, and MCP-based tool ecosystems.

• Work with business stakeholders to understand problem statements and translate them into AI-enabled solutions.

• Perform testing, validation, and evaluation of LLM outputs, including applying guardrails and quality checks.

• Maintain documentation for prompts, workflows, tools, and AI system behaviors.

• Participate in Agile ceremonies and sprint activities within the AI engineering team.

Education

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  Bachelor’s degree in computer science, AI/ML/DS, Information Systems, Engineering, or a related field.

• Strong understanding of Python (preferred) or another major programming language (JavaScript/TypeScript, Java, etc.).

• Familiarity with foundational AI concepts:

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  LLMs

• Embeddings

• Vector databases

• Prompt engineering

• Retrieval workflows (RAG)

• Experience with API development or integrating with REST-based services.

• Exposure to cloud platforms such as Azure (preferred), AWS, or GCP.

• Strong analytical and problem-solving skills.

• Good communication, a learning mindset, and the ability to collaborate with cross-functional teams.

Experience using Agentic AI frameworks such as:

• 
  LangChain

• LangGraph

• Azure AI Agent Services

• Familiarity with MCP (Model Context Protocol) concepts and tool integrations.

• Basic understanding of vector search (Azure AI Search, Pinecone, FAISS).

• Experience with GitHub Copilot, OpenAI Vibe Coding, or similar AI coding assistants.

• Knowledge of cloud-native development (Functions, Storage, APIM, serverless patterns, Azure App Services).

• Understanding common AI safety and governance principles.

• Exposure to agile development practices.