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About This Role
Job no: 532278
Brand: Product and Technology
Work type: Full time
Location: Texas
Categories: Digital and Technology
AI Developer \- Forward Deployed Engineer
Flight Centre Travel Group (FCTG) is one of the world’s largest travel retailers and corporate travel managers. The company, which is headquartered in Brisbane, Australia has company\-owned leisure and corporate travel business in 23 countries, spanning Australia, New Zealand, the Americas, Europe, the United Kingdom, South Africa, the United Arab Emirates and Asia. FCTG also operates a global corporate travel management network, which extends to more than 90 countries through company\-owned businesses and independent licensees. The company opened its first leisure travel shop in Sydney, Australia in 1982 and listed on the Australian Securities Exchange in 1995\. Our purpose is to “open up the world for those who want to see”. Every day, we give people all around the world the opportunity to experience something really amazing – travel!
To learn more about Flight Centre Travel Group please click HERE
About the Opportunity
Join FCTG's AI Strategy \& Integration (ASI) team and help shape the future of agentic AI in travel. As an AI Developer and Forward Deployed Engineer, you'll build headless AI capabilities for Sam and Mel, enabling seamless integration with external agents, platforms, and customer environments through emerging agent\-to\-agent protocols. You'll play a unique dual role, combining deep technical integration work with direct customer engagement, ensuring real\-world success for enterprise AI deployments. This is an opportunity to work at the forefront of AI interoperability, customer innovation, and next\-generation travel technology.
KEY RESPONSIBILITIES
- Build headless versions of Sam and Mel that expose booking, servicing, proactive, and profile capabilities to external agents and platforms.
- Design APIs and services that can be driven through MCP, A2A, ACP, and CLI interfaces.
- Develop wrappers and adapters that enable seamless protocol\-based integrations.
- Implement and maintain integrations across MCP, A2A, and ACP ecosystems.
- Assess and design optimal interactions between agents, tools, and underlying systems.
- Establish secure integration frameworks with robust access controls and governance.
- Embed with enterprise customers to implement and optimize AI integrations in production environments.
- Translate complex customer requirements into scalable technical solutions.
- Serve as a trusted technical advisor to customer engineering and travel\-management teams.
- Partner with internal stakeholders to improve product capabilities based on customer feedback and deployment learnings.
- Share technical best practices and lead solution discussions with customers and internal teams.
- Contribute to a safe, inclusive, and accessible work environment where all Flighties feel welcomed, respected, and supported to thrive.
- Other duties and tasks as assigned
- Contribute to a safe, inclusive, and accessible work environment where all Flighties feel welcomed, respected, and supported to thrive
EXPERIENCE \& QUALIFICATIONS
- 3\-6 years of software engineering or AI engineering experience with strong integration expertise.
- Deep hands\-on experience with MCP and A2A frameworks.
- Familiarity with ACP and broader agent\-to\-agent protocol ecosystems preferred.
- Experience designing APIs and building protocol wrappers and adapters.
- CLI development experience is advantageous.
- Knowledge of LLM application patterns including RAG, tool calling, and agent orchestration.
- Strong customer\-facing and client\-embedded implementation experience.
- Excellent presentation and stakeholder communication skills.
- Analytical mindset and ability to thrive in fast\-moving, ambiguous environments.
- Ability and willingness to travel to customer sites.
- Located within a North American time zone.
- Bonus experience within corporate travel or travel technology.
- Experience with Claude Code, Langfuse, LangChain, Datadog, Python, JavaScript, AWS, Google Cloud, GitHub Actions, and/or Argo CD is beneficial.
Work Perks! \- What’s in it for you:
FCTG is renowned internationally for having amazing perks and an even better culture. We understand that our people are our most valuable asset. It is the passion and dedication of our teams that keep the company on top of the industry ladder. It’s also why we offer some great employee benefits and perks outside of the norm.
- Have fun: At the heart of everything we do at Flight Centre is a desire to have fun.
- Reward \& Recognition: Celebrate the success of yourself and others at our regular Buzz Nights and at the annual Global Gathering \- You'll have to experience it to believe it!
- Use your smarts: Our people use their quick thinking, expertise, and tenacity to always figure things out.
- Love for travel: We were founded by people who wanted to travel and want others to do the same. That passion is something you can’t miss in our people or service.
- Personal connections: We are a big business founded on personal relationships.
- Diversity, Equity \& Inclusion: Commitment to diversity, equity, and inclusion through initiatives like Diversity Day (paid leave to observe a holiday or cultural celebration of your choice) Employee Resource Groups (Racial Equity, Gender Equity, LGBTQ2IA\+, Accessibility, Environmental Justice), DEI education initiatives, and equitable practices, including regular equity assessments and inclusive recruitment protocols.
- A career, not a job: We offer genuine opportunities for people to grow and evolve
- We back our people all the way: We are strongly committed to supporting every single employee in their professional and personal development.
- Giving Back: Our Corporate Social Responsibility program supports nominated charities through volunteering and fundraising, complemented by our Office Environmental Program, LEED® Gold\-certified office spaces, and 1 paid Volunteer Day per calendar year.
Benefits Include:
- Paid Time Off: A comprehensive time off package, including up to 15 vacation days (prorated upon hire and increasing to 20 days after 2 years of employment), 5 sick days, 3 personal days, 1 Diversity Day, 1 Volunteer Day, and 9 recognized holidays annually.
- Travel perks/discounts
- Health \& Wellness Programs and Employee Financial Wellness Services
- National/International Award Nights and Conferences
- Health benefits including, medical, dental, vision, gender affirming care, and fertility care
- Insurance including hospital indemnity, AD\&D, critical illness, long\-term and short\-term disability
- Flexible Spending Accounts
- Employee Assistance Program
- 401k program with partial match
- Tuition Reimbursement Program
- Employee Share Plan – Ability to purchase company stock on Australian Stock Exchange with partial company match, subject to terms and conditions
- Global career opportunities in a network of brands and businesses
- Vacation, Personal, and Sick time accrual rates will vary based on full\-time or part\-time employee status. Recognized Holidays are either paid time off or, if required to work due to job requirements, holiday pay rate, and may vary depending on state.
Location – Houston, TX
Open to applicants located in Austin, TX.
If this sounds like the opportunity you have been waiting for then .
Internal Postings ONLY \- Have questions about this opportunity? Reach out to our recruitment team at [email protected]
For this position, we anticipate offering an annual salary of $150,000 \- $190,000\. Base salary is dependent on relevant factors, including experience, geographic location, and job requirements.
EXTERNAL POSTINGS ONLY *\-* We thank all candidates for their interest; however, only those selected to continue in the process will be contacted.
INTERNAL ONLY \- Before applying to any internal position you must have been with the company or your current role for a minimum of 6 \- 12 months and notify your leader prior to applying.
Our number one philosophy? Our people. Flight Center Travel Group USA’s promise is to provide an environment with equality of respect, dignity and opportunity for all our employees. We value an inclusive and supportive workplace which truly reflects the diversity of our society.
We are an affirmative action and equal opportunity employer committed to providing a barrier\-free pathway throughout our recruitment process. We welcome accommodation requests to help make our hiring and onboarding experience as accessible as possible. Please advise us about accommodation needs at any point by contacting our Recruitment Team at [email protected]
GBTA WINiT Top 50 Award Recipients (2018–2025\)
CHHR: 5\-Star DE\&I Employer (2023, 2024, 2026\)
Seramount, FCTG Mexico: Member of the Global Inclusion Index (2023–2025\)
Newsweek: America’s Greatest Workplaces for Diversity (2024\)
Benefits Canada: Health/Wellness Program and Mental Health Program (2023, 2025\)
✈️ OutThere Awards: Inclusive Travel Finalist (2025\)
Canadian HR Awards: Excellence in Diversity and Inclusion Awardee (2025\)
2026 Disability Index®: *World’s Top Disability Inclusive Business*
\#LI\-KB1\#LI\-Onsite
Applications close: 18 Sep 2026 Central Daylight Time
Salary Context
This $150K-$190K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Flight Centre Travel Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($170K) sits 21% below the category median. Disclosed range: $150K to $190K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Flight Centre Travel Group AI Hiring
Flight Centre Travel Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Houston, TX, US. Compensation range: $190K - $190K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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