Full-Time
AI Engineer
Digital
Updated on 9/10/2026
Airbus
10,001+ employees
Manufacturer of commercial aircraft, helicopters, defense
No salary listed
Bengaluru, Karnataka, India
In Person
Bachelor's, Master's
 AI & Machine Learning (1) |
|---|
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- A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related quantitative field.
- At least one recognized cloud or AI certification, such as Google Cloud Professional Machine Learning Engineer or an equivalent advanced AI or cloud credential.
- Four to seven years of hands-on experience building, deploying, and scaling end-to-end artificial intelligence and machine learning products, generative artificial intelligence applications, code transformation tools, and intelligent software automation systems.
- Extensive expertise in Google Cloud Platform, including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and Google Kubernetes Engine.
- Strong proficiency applying large language models, retrieval-augmented generation architectures, vector databases, and frameworks such as LangChain or LlamaIndex.
- Mastery of Python and solid proficiency with RESTful application programming interfaces, gRPC, microservice design patterns, and modern frontend frameworks.
- Familiarity with abstract syntax trees, static code analysis, compiler concepts, or domain-specific language translation techniques.
- Hands-on experience with MLOps workflows, model tracking, automated testing, containerization using Docker and Kubernetes, and continuous integration and continuous delivery pipelines.
- Proven experience with token metering, cost attribution, model routing policies, and monitoring tools such as OpenTelemetry and Cloud Monitoring.
- Ability to translate complex client or internal business requirements into practical, scalable AI features with measurable return on investment.
- Ability to explain complex AI and machine learning mechanics to non-technical business leaders and senior technical stakeholders.
- Ability to work in an ambiguous, lab-oriented environment where novel user experience and software engineering paradigms must be developed.
- Understanding of engineering pain points and ability to translate legacy technical debt into streamlined digital products.
- Architect, build, and deploy production-grade AI-driven products that automate complex engineering workflows, accelerate software transformation, and support intelligent digital paradigms.
- Lead the lifecycle of advanced AI products, including architectural design, model selection and fine-tuning, production deployment, monitoring, and performance optimization.
- Design and implement intelligent systems that parse, translate, and modernize complex legacy codebases and technical documentation using natural language processing and large language models.
- Develop prompt architectures, retrieval-augmented generation pipelines, and fine-tuned models to automate domain-specific artifact generation and technical decision-making from high-level user prompts.
- Use Google Cloud Platform infrastructure to build resilient, serverless, and scalable AI microservices and batch-processing pipelines.
- Partner with Product Managers, UX Designers, Software Architects, and Domain Experts to ensure technical feasibility, clear system requirements, and integration into enterprise ecosystems.
- Establish continuous integration and continuous delivery pipelines for AI assets, automated testing frameworks, robust application programming interface design, and technical documentation.
- Promote an innovation-focused engineering culture, track emerging generative AI and machine learning research, and mentor junior team members on production machine learning engineering practices.
- Implement granular tagging, billing telemetry, and cost-attribution frameworks for AI workloads on Google Cloud Platform.
- Monitor, analyze, and optimize model inference costs, including token-based application programming interface spend, vector database queries, and graphics or tensor processing unit utilization.
- Prior experience building source-to-source compilers, automated code conversion utilities, or automated design-document generators.
- Familiarity with software architecture patterns, legacy enterprise frameworks, and multi-language code-conversion strategies.
- Knowledge of quantitative product analytics for tracking AI feature adoption, model accuracy, and user-efficiency improvements.
- An active GitHub profile or portfolio demonstrating end-to-end AI applications, open-source contributions, or custom large-language-model tooling.
Airbus designs and manufactures commercial airplanes, helicopters, military aircraft, and space systems like satellites and launch services. The company builds these products by integrating advanced airframes, propulsion systems, and digital communication networks to support global travel, defense, and scientific exploration. Airbus distinguishes itself through its massive global manufacturing network and its active development of hydrogen-powered aircraft to eliminate carbon emissions. Its goal is to provide safe, connected aerospace solutions while leading the industry toward sustainable flight and environmental responsibility.
Company Size
10,001+
Company Stage
IPO
Headquarters
Blagnac, France
Founded
1970
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Simplify's Take
What believers are saying
- Airbus raised H1 2026 revenue 12% to €33.2 billion and doubled net profit.
- Airbus maintained 2026 guidance at about 870 deliveries and €7.5 billion EBIT.
- Defence and Space EBIT jumped 84% in H1 2026, strengthening margins and diversification.
What critics are saying
- Spanish unions struck Airbus plants in August 2026, exposing fragile labor relations and morale.
- Boeing's challenge to Airbus's €3 billion EIB loan threatens R&D funding through 2030.
- Pratt & Whitney engine shortages already cut deliveries; another supplier shock would crush 2026 guidance.
What makes Airbus unique
- Airbus's 9,222-jet backlog gives it unmatched visibility into production through 2035.
- Qantas chose Airbus A350-1000ULR for Project Sunrise, reinforcing long-range engineering leadership.
- Airbus and MTU's hydrogen fuel-cell venture targets next-generation propulsion, not incremental tweaks.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
Paid Vacation
Parental Leave
401(k) Retirement Plan
Employee Stock Purchase Plan
Professional Development Budget
Flexible Work Hours
Growth & Insights and Company News
6 month growth
↑ 3%1 year growth
↑ 3%2 year growth
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Airbus has postponed its plan to reduce remote working after strikes by Spanish unions, Reuters reports. The aerospace manufacturer will allow employees to continue working from home an average of two days per week, shelving indefinitely a push to limit remote work to one day. Chief Executive Guillaume Faury had sought to require white-collar staff on-site four days weekly by September, citing the need for knowledge transfer. Spanish unions said roughly 40% of Airbus's 14,000 Spanish employees have walked out over remote work policies, transport, leave and wages. An Airbus spokesperson said the company would implement the transition "more gradually" based on employee feedback. French unions estimate a quarter to a third of Airbus's workforce has been hired in the past three years. Aircraft production has not been affected by the disruptions.
The European Investment Bank's €3 billion loan to Airbus has sparked a dispute between Boeing and the EU. Boeing has asked the US government to challenge the loan package, which will fund aircraft research and development through 2030. The first tranche of €1 billion has already been signed. Boeing claims the loan — the EIB's largest ever corporate financing — may violate a 2021 truce agreement between the rivals. US Trade Representative Jamieson Greer said his office is examining the loan and has raised concerns with EU officials. The EIB and Airbus both maintain the loan operates on standard market terms. Airbus CFO Thomas Toepfer stated the financing was secured completely on market conditions.
Airbus reported second-quarter revenue of €20.5 billion, up 28% year-on-year, with adjusted EBIT climbing 54% to €2.43 billion. Net income rose 126% to €1.66 billion. The commercial aircraft division saw revenue increase 37% to €15.4 billion, whilst reported EBIT surged 150% to €1.95 billion. Airbus Defence and Space revenue grew 10% to €3.48 billion, with reported EBIT more than doubling to €408 million. Chief executive Guillaume Faury said strong deliveries reflected steady execution as the company ramps up production. Airbus maintained its forecast of approximately 870 commercial aircraft deliveries for 2026. The Toulouse-based manufacturer delivered 351 aircraft in the first half, having faced engine supply constraints and parts shortages earlier in the year.
Airbus reported first-half revenue of €33.2 billion, up 12% year-on-year, driven by a rebound in commercial aircraft deliveries. Second-quarter adjusted EBIT rose 54% to €2.43 billion, beating analyst expectations of €2.19 billion. Net profit more than doubled to €1.66 billion from €732 million. The company delivered 351 commercial aircraft in the first six months, up from 306 in H1 2025. Its defence and space segment posted an 84% increase in adjusted EBIT to €487 million. Airbus maintained its full-year guidance of around 870 aircraft deliveries and adjusted EBIT of approximately €7.5 billion. The strong second quarter marks a turnaround after first-quarter profit fell 52% amid supply constraints from engine maker Pratt & Whitney.