Senior AI Engineer

Digital Realty

111d

About The Position

As a Backend & Multi-Agent AI Services developer, you will build and maintain backend services using Azure Functions, Semantic Kernel, LangChain/LangGraph/AutoGen/CrewAI. Your role will involve developing APIs to orchestrate LLM workflows, manage state, and support chat and analytics front ends. You will implement multi-agent pipelines with planning, reasoning, and execution flows, while optimizing performance, latency, and token usage with robust error handling and scalable design. In the RAG, Data, & AI Pipelines aspect, you will design and manage RAG pipelines, extending retrieval with GraphRAG and entity-driven reasoning. You will build ingestion pipelines to validate, clean, and test data before adding it to the AI knowledge layer, integrating data from various sources such as CosmosDB, Dataverse, APIs, Azure Cognitive Search, and SharePoint. Additionally, you will create automated evaluation methods for retrieval accuracy, hallucination, and dataset quality. In collaboration with front-end engineers, you will define API contracts, payloads, and session flows to support full-stack applications, providing reusable backend services, SDKs, and documentation. You will align backend services with React, Next.js, and shadcn frameworks for modern enterprise UIs. Furthermore, you will implement telemetry for latency, retrieval hit/miss, hallucination, cost, and user engagement, integrating logging and metrics with observability tools like OpenTelemetry, Prometheus, and Grafana. Security measures will include enforcing RBAC, compliance, and secure handling of enterprise data, including masking, sanitization, and lineage tracking.

Requirements

• Strong hands-on experience with Azure AI/data stack: Cognitive Search, Azure OpenAI, CosmosDB, Azure Functions, AKS, Dataverse.
• Proficiency in Python and backend frameworks (FastAPI/Flask/Django).
• Experience with RAG pipelines, multi-agent frameworks (LangChain, LangGraph, AutoGen, CrewAI), and Semantic Kernel.
• Familiarity with vector stores (FAISS, Pinecone, Weaviate, Azure Cognitive Search).
• Working knowledge of React/Next.js to support API integration with UIs.
• 4+ years in backend, ML infrastructure, or cloud engineering.
• 2+ years building AI/LLM-based applications, ideally in enterprise environments.
• Proven experience integrating multiple enterprise data sources securely.
• Background in data quality testing, validation, and continuous evaluation for AI systems.
• Exposure to full-stack development with React/Next.js.

Nice To Haves

• Experience with GraphRAG, knowledge graphs, and entity-based retrieval.
• Experience with continuous LLM evaluation (DeepEval, G-Eval, custom pipelines).
• End-to-end experience building full-stack AI solutions (backend + React/Next.js front end).

Responsibilities

• Build and maintain backend services using Azure Functions, Semantic Kernel, LangChain/LangGraph/AutoGen/CrewAI.
• Develop APIs to orchestrate LLM workflows, manage state, and support chat and analytics front ends.
• Implement multi-agent pipelines with planning, reasoning, and execution flows.
• Optimize performance, latency, and token usage with robust error handling and scalable design.
• Design and manage RAG pipelines (chunking, embedding, indexing, hybrid retrieval).
• Extend retrieval with GraphRAG and entity-driven reasoning.
• Build ingestion pipelines to validate, clean, and test data before adding it to the AI knowledge layer.
• Integrate data from CosmosDB, Dataverse, APIs, Azure Cognitive Search, SharePoint, and other enterprise sources.
• Create automated evaluation methods for retrieval accuracy, hallucination, and dataset quality.
• Collaborate with front-end engineers to define API contracts, payloads, and session flows.
• Support full-stack applications by providing reusable backend services, SDKs, and documentation.
• Align backend services with React, Next.js, and shadcn frameworks for modern enterprise UIs.
• Implement telemetry for latency, retrieval hit/miss, hallucination, cost, and user engagement.
• Integrate logging and metrics with observability tools (OpenTelemetry, Prometheus, Grafana).
• Enforce RBAC, compliance, and secure handling of enterprise data, including masking, sanitization, and lineage tracking.

Benefits

• Highly competitive compensation package.
• Excellent benefits.
• Supportive and inclusive environment.
• Development opportunities for career growth.

What This Job Offers

• Industry: Real Estate