AI Backend Software Engineer II - AI Application Platform
Role details
Job location
Tech stack
Job description
As a Software Engineer working on the AI Application Platform, you will work at the intersection of scalable backend systems and cutting-edge AI. You will have the opportunity to design and build the core platform that enables product teams to rapidly develop and deploy AI-powered experiences for millions of people. You will tackle complex performance and scaling challenges, shape the foundation of our AI infrastructure, and collaborate closely with ML engineers, data engineers, and data scientists to bring intelligent systems into production at scale., Important aspects of the job can include:
- Design and evaluate architecture solutions for AI infrastructure, rapidly prototyping to validate key assumptions and guide decision-making.
- Explore, benchmark, and integrate new AI/ML tools and technologies to drive innovative engineering solutions that meet evolving business needs.
- Build and maintain scalable, reusable backend services that support real-time AI/ML inference, model deployment, and data pipelines.
- Collaborate closely with ML engineers, data engineers, and data scientists to bring AI/ML models into production and optimize system performance.
- Take end-to-end ownership of system reliability and operational excellence, including performance tuning, observability and incident management.
- Continuously grow technical and interpersonal skills through hands-on experience, knowledge sharing sessions, and industry events.
Requirements
Do you have experience in Spark?, Do you have a Master's degree?, We are looking for driven Software Engineers who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right approach and tools., * 3+ years of professional experience in software engineering, with a focus on backend or platform development.
- Experience building distributed systems at scale, with a focus on performance tuning, observability, and reliability best practices.
- Experience with scalable data storage systems (e.g. MySQL, Redis) and optimizing data access and caching for high-throughput applications.
- Proficiency in one or more server-side programming languages such as Java, Scala, or Python.
- Experience in feature engineering, integrating AI/ML models into production systems, and understanding model behavior, performance and constraints.
- Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration.
- Experience working in cross-functional teams alongside ML engineers, data scientists, and product stakeholders to bring AI/ML products to production.
- Experience with containerization tools like Docker and Kubernetes, and deploying applications in cloud environments such as AWS or GCP.
- Ability to navigate ambiguity, take ownership of complex problems, and drive them to resolution.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent industry experience., Docker, Kubernetes, AWS, GCP, Cost optimization, Flink, Stream processing, Spark, Batch processing, Weaviate, Pinecone, Milvus, Qdrant, Chroma,Vector search, Semantic search, Embeddings, MySQL, PostgreSQL, AWS RDS, Amazon Aurora, Oracle, MS SQL Server, Redis, AWS Elasticache, Memcached, Feature Engineering, Feature Store, Grafana, Prometheus, Arize, Dashboards and alerts, Python, Java, Scala, N8n, Temporal.io, Cadence, Workflow orchestration, Agent Orchestration, MCP, A2A,ACP, TAP, OAP, FCP, GPT, Claude, Grok, Llama, Gemini, Qwen, R1, Prompt Engineering, LLM Evals, RAG, Guardrails, Memory, Multimodal, Agentic system design, Agentic AI, system design, AI Agents design, Agentic design pattern, Context engineering, Scaling LLM inference, Search and Ranking, Recommendation Systems, Optimization and Causal Inference, LLMs and Natural Language Understanding, Computer Vision, Speech and Multimodal AI, Reinforcement Learning, Generative AI
Benefits & conditions
- Annual paid time off and generous paid leave scheme including: parental (22-weeks paid leave), grandparent, bereavement, and care leave.
- Hybrid working including flexible working arrangements, working from home furniture and ergonomic support, and up to 20 days per year working from abroad (home country).
- A beautiful sustainable HQ Campus in Amsterdam, that offers on-site meals, coffee, and snacks, multi-faith and breastfeeding rooms at the office.
- Commuting allowance and bike reimbursement scheme.
- Discounts & Wallet credits to spend on our products, upgrade to Booking.com Genius Level 3, and friends & family Booking.com discount vouchers.
- Free access to online learning platforms, development and mentorship programs.
- Global Employee Assistance Program, free Headspace membership.
#ThinkInclusion: Diversity, Equity and Inclusion at Booking.com Diversity, Equity and Inclusion (DEI) have been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations. Take it from our Chief People Officer, Paulo Pisano: "At Booking.com, the diversity of our people doesn't just create a unique workplace, it also creates a better and more inclusive travel experience for everyone.
