Software Development Engineer III - Back End, GenAI Platform

Expedia•Chicago, IL

46d•Hybrid

About The Position

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. The Software Developer III role is part of the GenAI Platform team. The GenAI Platform team builds and operates Expedia Group’s shared generative AI platform - tooling, services, and guardrails - that enable product and ML teams to safely experiment with, deploy, and scale GenAI-powered experiences across our brands. You will design and deliver backend services powering AI capabilities across Expedia Group. You’ll write production code, mentor junior engineers, and drive well-scoped projects from design through delivery. The role blends core software engineering fundamentals with hands-on work in the GenAI stack—RAG pipelines, vector stores, LLM integrations, and platform guardrails.

Requirements

Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
5+ years of relevant professional experience.
Proven experience building and operating backend APIs and services in a cloud environment, preferably AWS, including automated testing, CI/CD pipelines, monitoring, logging, and participation in on-call rotations.
Strong proficiency in Python and experience with FastAPI or similar web frameworks (such as Flask, Django, or other asynchronous frameworks), with solid understanding of software design principles, data structures, and design patterns.
Hands-on experience with at least one data store technology (relational, NoSQL, or search), with familiarity using systems like PostgreSQL or Elasticsearch to support service-level data modeling and persistence.

Nice To Haves

Experience designing and operating internal platforms, shared services, or SDKs that are consumed by multiple teams, including clear technical documentation (design docs, runbooks, integration guides) and data-driven iteration.
Prior exposure to or hands-on work with LLM-powered systems and GenAI concepts such as prompting, embeddings, retrieval-augmented generation (RAG), vector stores, and associated evaluation or observability frameworks.
Demonstrated ability to apply AI/ML and GenAI patterns safely within production services, including implementing and evolving guardrails, evaluations, and operational practices for AI/ML‑enabled solutions at scale.
Experience with RAG or vector store tooling (for example, LangChain, LlamaIndex, LangGraph) and familiarity with workflow or agent orchestration systems (such as n8n, Flowise, or similar) to integrate AI-driven capabilities into backend service architectures.
Background working with multiple programming languages and understanding their trade-offs for different backend and data-intensive workloads, with a track record of making pragmatic, data-informed technical decisions.

Responsibilities

Design, build, test, and operate Python- and FastAPI-based backend services and APIs that power GenAI Platform capabilities, including RAG Manager, RAG Data Plane, and vector store services.
Implement sound system design (including low-level design), API design, and data modeling for backend services that are reliable, secure, and easy for internal customers to adopt.
Integrate backend services with LLM providers, Elasticsearch-based vector stores, and Aurora PostgreSQL as part of Expedia Group’s RAG and GenAI platform stack, ensuring robust and observable data and inference flows.
Contribute to and enhance platform guardrails and safety features such as authentication, API key management, workload-to-workload authorization, evaluation hooks, and monitoring to keep GenAI applications responsible and compliant.
Safely integrate and operate AI/ML‑enabled solutions, tools, and workflows that improve developer and traveler outcomes, including familiarity with AI‑driven systems and applying foundational AI/ML concepts to real-world platform products.
Own well-scoped projects end-to-end—from technical design and implementation through rollout, documentation, and post-launch improvements—while mentoring junior engineers and collaborating closely with staff/principal engineers, product managers, and applied scientists.