MetLife

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.