Job description

This is a temporary position. The assignment duration is through September 11, 2027. JOB SUMMARY Marriott International is a global hospitality company with a portfolio of 31 brands and more than 8,500 properties across 138 countries and territories. Diversity, inclusion, and the well-being of associates are fundamental to Marriott's values and business goals. The FLEX Software Engineer, Conversational AI and Intelligent Search designs, builds, tests, and operates production-grade conversational AI and intelligent search experiences that deliver accurate, reliable, secure, and personalized customer interactions. This role develops AI agents, retrieval workflows, backend services, APIs, and integrations, applying scalable architecture, structured tool use, evaluation, observability, security, and operational reliability to move generative AI solutions from concept to production. CANDIDATE PROFILE Education and Experience Required • Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or high school diploma/GED with an additional 4 years of professional experience. • 2+ years of professional software engineering experience. • Programming experience in Python, Java, JavaScript, TypeScript, or a comparable language, with demonstrated experience building and operating production backend services, APIs, cloud-native applications, containers, Kubernetes, distributed systems, and automated CI/CD pipelines. • Hands-on experience developing generative AI, conversational AI, intelligent search, retrieval-augmented generation, or agent-based applications, including model APIs, prompt engineering, tool calling, structured outputs, embeddings, retrieval, context management, testing, observability, secure development, and sensitive-data handling. Preferred • Experience building multi-agent or workflow-orchestrated AI systems using frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, Temporal, or comparable technologies. • Experience with vector databases, hybrid search, reranking, retrieval optimization, AI evaluation, LLM-as-judge patterns, experimentation, latency and token optimization, caching, and cost management. • Experience with responsible AI, prompt-injection defenses, content safety, red-team testing, OpenTelemetry, application-performance monitoring, canary deployments, feature flags, progressive delivery, and localized, accessible, high-traffic customer applications. CORE WORK ACTIVITIES • Designs, builds, tests, deploys, and operates production-grade conversational AI applications, intelligent search experiences, and AI agents. • Develops multi-turn workflows, agent routing, structured tool calling, memory, and context-management capabilities. • Builds retrieval-augmented generation and intelligent search solutions using embeddings, vector retrieval, hybrid search, reranking, and grounding techniques. • Integrates AI applications with internal APIs, search platforms, databases, model providers, and external services. • Develops scalable APIs, streaming interfaces, asynchronous workflows, and event-driven backend services. • Implements prompt management, model configuration, structured outputs, safety guardrails, authentication, authorization, and secure data-handling practices. • Improves response accuracy, grounding, relevance, personalization, latency, scalability, and cost efficiency through measurement and iterative engineering. • Creates unit, integration, contract, end-to-end, and automated regression tests for AI applications and supporting services. • Partners with Quality Engineering to develop evaluation datasets, release-quality thresholds, and repeatable AI evaluation and experimentation practices. • Implements logging, metrics, distributed tracing, alerting, dashboards, and production diagnostics using OpenTelemetry and application-performance monitoring platforms. • Troubleshoots complex production issues across models, prompts, application code, infrastructure, data stores, and downstream dependencies, and performs root-cause analysis. • Participates in architecture reviews, code reviews, release planning, CI/CD implementation, progressive delivery, and production support. • Evaluates emerging generative AI technologies and makes pragmatic architecture and implementation decisions aligned with business, security, reliability, and operational requirements. • Collaborates across Product, Engineering, Quality Engineering, Security, Platform, and Operations teams to deliver inclusive, accessible, and high-traffic customer experiences. At Marriott International, we are dedicated to being an equal opportunity employer, welcoming all and providing access to opportunity. We actively foster an environment where the unique backgrounds of our associates are valued and celebrated. Our greatest strength lies in the rich blend of culture, talent, and experiences of our associates.  We are committed to non-discrimination on any protected basis, including disability, veteran status, or other basis protected by applicable law.

Requirements

Must-haves

This is a temporary position.
The assignment duration is through September 11, 2027.
Education and Experience
Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or high school diploma/GED with an additional 4 years of professional experience.
2+ years of professional software engineering experience.
Designs, builds, tests, deploys, and operates production-grade conversational AI applications, intelligent search experiences, and AI agents.
Develops multi-turn workflows, agent routing, structured tool calling, memory, and context-management capabilities.
Builds retrieval-augmented generation and intelligent search solutions using embeddings, vector retrieval, hybrid search, reranking, and grounding techniques.
Integrates AI applications with internal APIs, search platforms, databases, model providers, and external services.
Develops scalable APIs, streaming interfaces, asynchronous workflows, and event-driven backend services.
Implements prompt management, model configuration, structured outputs, safety guardrails, authentication, authorization, and secure data-handling practices.
Improves response accuracy, grounding, relevance, personalization, latency, scalability, and cost efficiency through measurement and iterative engineering.
Creates unit, integration, contract, end-to-end, and automated regression tests for AI applications and supporting services.
Partners with Quality Engineering to develop evaluation datasets, release-quality thresholds, and repeatable AI evaluation and experimentation practices.
Implements logging, metrics, distributed tracing, alerting, dashboards, and production diagnostics using OpenTelemetry and application-performance monitoring platforms.
Troubleshoots complex production issues across models, prompts, application code, infrastructure, data stores, and downstream dependencies, and performs root-cause analysis.
Participates in architecture reviews, code reviews, release planning, CI/CD implementation, progressive delivery, and production support.
Evaluates emerging generative AI technologies and makes pragmatic architecture and implementation decisions aligned with business, security, reliability, and operational requirements.
Collaborates across Product, Engineering, Quality Engineering, Security, Platform, and Operations teams to deliver inclusive, accessible, and high-traffic customer experiences.

Nice-to-haves

Experience building multi-agent or workflow-orchestrated AI systems using frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, Temporal, or comparable technologies.
Experience with vector databases, hybrid search, reranking, retrieval optimization, AI evaluation, LLM-as-judge patterns, experimentation, latency and token optimization, caching, and cost management.

Application prep

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Keywords to mirror

aipythonjavajavascripttypescriptkubernetesci/cdllm

Platform: oracle-cloud
Effort: medium