AI Engineer – IS/IT International
Thales is hiring an AI Engineer – IS/IT International in Jakarta, Indonesia. Level rates it ; you can apply on Thales.
Level's read on this job
- Level rates this AI engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions prompt engineering, RAG and MLOps among its tools and skills.
- Level classes it as a mid-level role.
- Thales has 3,500+ other open roles on Level.
- Posted in the last few days.
AI in this role
Thales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we’re driven by a mission to build a future we can all trust.
Thales has been present in the Republic of Indonesia for 45 years in the defence, aerospace and space domains, delivering a wide range of civil and defence solutions that highlight our strong commitment to working with the Indonesian government and local stakeholders. In recent years, our innovative solutions in air traffic management systems and telecom satellites have further strengthened our presence in the country alongside our digital portfolio of solutions such as biometrics, data protection and cybersecurity now serving the needs of diverse customers in civil sectors.Key Responsibilities
1. AI Solution Development & Deployment
- Design, develop, test, and deploy AI applications, including generative AI assistants, knowledge search solutions, workflow automation, and machine learning use cases.
- Translate business requirements into technical designs and working solutions, from proof of concept through production deployment.
- Integrate AI solutions with enterprise applications, approved AI platforms, APIs, and business data sources.
- Implement evaluation methods to assess accuracy, relevance, reliability, and business suitability.
- Develop reusable components and deployment practices that support adoption across regions.
2. Business Engagement & Value Delivery
- Work with business stakeholders to identify challenges and assess where AI can deliver practical benefits.
- Evaluate use cases based on business value, feasibility, data readiness, cost, and risk.
- Define success criteria and track outcomes such as time saved, improved quality, adoption, and operational efficiency.
- Support demonstrations, user testing, training, and adoption.
- Act as an accessible IS/IT partner, helping business teams navigate AI opportunities and use approved capabilities.
3. IS/IT AI Vision & Regional Roadmap
- Contribute to a shared AI vision and roadmap for AMEWA, Asia, and India.
- Assess existing initiatives, capabilities, and business needs across the three regions.
- Identify opportunities to reuse solutions, share knowledge, and coordinate related initiatives.
- Align regional delivery with Group AI strategy, architecture, and approved platforms.
- Collaborate with the AI Champions program to communicate business needs and connect them with relevant Group capabilities.
4. Production Operations & Continuous Improvement
- Monitor deployed AI solutions for availability, performance, output quality, usage, and cost.
- Troubleshoot incidents and maintain reliable integrations and data flows.
- Implement version control, automated testing, and CI/CD practices for AI applications.
- Establish operational documentation, support procedures, and clear ownership before production release.
- Improve solutions based on user feedback, evaluation results, and changing business requirements.
5. Security, Governance & Knowledge Sharing
- Work with cybersecurity, data protection, architecture, and relevant governance teams throughout delivery.
- Apply appropriate access controls, data handling practices, human oversight, and safeguards against misuse.
- Document solution designs, data dependencies, evaluation results, limitations, and operating procedures.
- Share practical guidance and reusable approaches with IS/IT colleagues and business teams.
Requirements Technical Skills
Must Have
- Strong proficiency in Python and software engineering practices.
- Hands-on experience developing AI or machine learning applications and deploying them into production.
- Practical experience with large language models, prompt design, retrieval-augmented generation (RAG), embeddings, and vector search.
- Experience integrating applications through REST APIs and connecting AI solutions to enterprise data sources.
- Experience with cloud platforms, preferably Microsoft Azure and enterprise AI services.
- Solid understanding of SQL, data preparation, and data quality.
- Experience with Git-based source control, automated testing, and CI/CD pipelines.
- Understanding of AI evaluation, monitoring, security, and responsible AI principles.
- Ability to assess trade-offs between solution quality, latency, scalability, and cost.
Nice to Have
- Experience with Azure AI services, Azure Machine Learning, or comparable enterprise AI platforms.
- Familiarity with Microsoft 365, Power Platform, and enterprise AI assistant capabilities.
- Experience with containerization, infrastructure automation, and MLOps or LLMOps practices.
- Experience with document processing, enterprise knowledge management, or workflow automation.
- Familiarity with ITSM platforms such as ServiceNow and delivery tools such as Jira and GitLab.
Soft Skills
- Strong analytical and problem-solving skills, with a practical focus on business outcomes.
- Ability to explain AI capabilities, limitations, and technical choices to nontechnical stakeholders.
- Excellent communication and stakeholder management skills.
- Ability to work independently and collaborate across functions, cultures, and time zones.
- Sound judgment when balancing innovation, operational reliability, and security.
- A continuous learning mindset and willingness to share knowledge.
- Professional fluency in English; French is a plus.
Education / Experience
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
- At least 3 years of relevant experience in software engineering, AI/ML engineering, or a related role, including hands-on AI solution delivery.
- Experience taking solutions from business requirements and prototyping through deployment and operational support.
- Experience working with business stakeholders to deliver measurable improvements.
- Experience working in Agile delivery environments.
- Experience collaborating in multinational organizations, preferably across multiple regions.
At Thales, we’re committed to fostering a workplace where respect, trust, collaboration, and passion drive everything we do. Here, you’ll feel empowered to bring your best self, thrive in a supportive culture, and love the work you do. Join us, and be part of a team reimagining technology to create solutions that truly make a difference – for a safer, greener, and more inclusive world.
How we rate this
AI Engineer – IS/IT International at Thales rates 72 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- Typical AI engineer job
- $183k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, ML Ops, AI Evaluation, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. You get your review by email within 24 hours.
Get new AI engineer jobs (Works on AI ●●●○ or higher) by email
One email a week with the new AI engineer jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Software Engineering roles that work on AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step