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