Software Development Engineer III (AI)

expediagroup

Gurgaon 5 Years Exp Posted 43d ago

Job Description

In this role, you will:

  • Design and build end-to-end AI products and deployment pipelines.

  • Own technical architecture for AI workflows including prompt engineering, RAG, and agentic systems

  • Develop and review backend services, APIs, and data pipelines powering AI products

  • Translate complex Finance problems into scalable AI system designs

  • Ensure AI solutions meet standards for performance, reliability, security, and governance

  • Drive production readiness including monitoring, logging, evaluation, and cost control

  • Establish best practices for AI development, deployment, and maintenance

  • Partner closely with Product and stakeholders to shape technical solutions

 

Experience and Qualifications:

  • Strong hands-on expertise in Python and SQL; Java preferred

  • 5+ years of development experience in an enterprise-level engineering environment increasing levels of technical expertise.

  • Proven experience building and deploying ML / AI / LLM-powered systems in production

  • Deep understanding of prompt engineering, RAG architectures, and agentic workflows

  • Experience with modern LLMs and frameworks such as OpenAI, Claude, Gemini, Llama, LangChain, Langflow, LlamaIndex, Semantic Kernel

  • Strong software engineering background: API design, distributed systems, system integration

  • Experience with data platforms, semantic modeling, and time-series logic

  • Good knowledge of Data Structures and Algorithm.

  • Solid understanding of cloud-native architectures, containers, and CI/CD pipelines

  • Experience with MLOps concepts such as monitoring, evaluation, and lifecycle management

  • Understanding of AI security, auditability, and compliance considerations

  • Ability to rapidly learn and apply new AI tools and technologies

  • AI products are designed and built for adoption across Finance teams

  • Systems scale reliably and are reusable across multiple use cases

  • AI solutions meet enterprise standards for trust, explainability, and governance

    • Technical execution consistently delivers measurable business impact​

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