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About This Role
Additional Information
Job Number26123877
Job CategoryInformation Technology
Location7750 Wisconsin Avenue, Bethesda MD 20814, United States
ScheduleFull Time
Located Remotely?Y
Position Type Management
Pay Range: $41.97-$69.23 per hour
Expiration Date: 10/14/2026 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, Software Development Engineer in Test, AI, leads quality engineering for production conversational AI and intelligent search experiences. This role combines software development in test, browser and API automation, AI evaluation, performance engineering, accessibility validation, and production reliability to establish measurable quality standards and release-readiness gates for accurate, grounded, secure, reliable, and consistent customer experiences.
CANDIDATE PROFILE Education and Experience*Required*
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent professional experience.
- 2+ years of experience in quality engineering, test automation, or SDET roles.
- Strong programming experience in Python, JavaScript, TypeScript, Java, or a comparable language, with hands-on experience in browser automation, API testing, automated test frameworks, performance testing, source control, code review, and CI/CD quality gates.
- Experience testing conversational AI, generative AI, retrieval-augmented generation, intelligent search, chatbot, or agent-based applications, including non-deterministic evaluation, cloud-native systems, containers, Kubernetes, observability, accessibility, and cross-functional delivery.
Preferred
- Experience with commercial or open-source LLM evaluation platforms and with designing LLM-as-judge, deterministic, human-evaluation, prompt-testing, model-comparison, and retrieval-ranking workflows.
- Experience with responsible-AI validation, red teaming, adversarial datasets, contract testing, service virtualization, workflow orchestration, asynchronous systems, canary deployments, and production smoke testing.
- Experience with localization, accessibility, responsive and cross-browser testing, authentication and authorization testing, CORS, CSP, sensitive-data security testing, quality dashboards, and executive release-readiness reporting.
CORE WORK ACTIVITIES* Defines and owns the automated quality strategy for conversational AI applications and intelligent search experiences.
- Builds and maintains browser, API, integration, contract, smoke, regression, and end-to-end automated test suites.
- Develops automated evaluations for response correctness, relevance, grounding, hallucination risk, retrieval quality, ranking quality, tool selection, and tool-call accuracy.
- Validates multi-turn conversation consistency, safety guardrails, prompt-injection resistance, responsible-AI requirements, and sensitive-data handling.
- Converts business scenarios, customer journeys, and production defects into reusable regression datasets and automated tests.
- Develops performance, load, stress, spike, scalability, and reliability tests for AI applications and supporting services.
- Establishes measurable quality baselines for latency, throughput, error rates, concurrency, resource utilization, and release readiness.
- Integrates automated tests, AI evaluations, and quality thresholds into CI/CD pipelines and progressive-delivery workflows.
- Builds automated pre-deployment and post-deployment smoke tests that validate critical customer and system workflows.
- Manages test environments, synthetic data, fixtures, service mocks, test credentials, and repeatable test execution capabilities.
- Analyzes failures and production issues using logs, metrics, distributed traces, automation results, and AI evaluation data.
- Produces quality dashboards, defect insights, evaluation summaries, and release-readiness reports for engineering and business stakeholders.
- Collaborates with Engineering, Product, Platform, Security, Accessibility, Quality Engineering, and Responsible AI teams to improve testability and prevent defects earlier in development.
- Evaluates emerging AI quality-engineering tools and techniques and applies pragmatic approaches appropriate for production systems.
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.
All locations offer 401(k) plan, stock purchase plan, discounts at Marriott properties, commuter benefits, employee assistance plan, and childcare discounts. Benefits are subject to terms and conditions, which may include rules regarding eligibility, enrollment, waiting period, contribution, benefit limits, election changes, benefit exclusions, and others. Click here to learn more.
Full-time positions also offer coverage for medical, dental, vision, health care flexible spending account, dependent care flexible spending account, life insurance, disability insurance, accident insurance, adoption expense reimbursements, and paid parental leave.
Washington Applicants Only: Employees will accrue paid sick leave, 0.0384 PTO balance for every hour worked and be eligible to receive minimum of 9 holidays annually.
Marriott Headquarters (HQ) supports a hybrid work environment that helps associates Be Connected. HQ based roles are generally hybrid and require regular in-office presence at the assigned location, including for candidates who live within commuting distance of HQ for a role listed as remote. Remote roles will be clearly identified in the job posting. Marriott International is the world’s largest hotel company, with more brands, more hotels and more opportunities for associates to grow and succeed. Be where you can do your best work, begin your purpose, belong to an amazing global team, and become the best version of you.
Salary Context
This $85K-$143K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $193K across 172 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Marriott International, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($114K) sits 48% below the category median. Disclosed range: $85K to $143K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Marriott International AI Hiring
Marriott International has 2 open AI roles right now. They're hiring across AI Software Engineer, AI Safety. Positions span Bethesda, MD, US, Bethesda, MD. Compensation range: $143K - $143K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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