Job Responsibilities
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.
Knowledge, Skills And Abilities
Education
- 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:
Experience
- 1–2 years of hands-on experience in AI/ML, Generative AI, or software engineering involving LLMs.
Knowledge and skills (general and technical)
- 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.
Other Requirements (licenses, Certifications, Specialized Training – If Required)
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.
