Senior Software Engineer – Backend, Big Data, AI

Akamai Technologies

. Design, develop, and deploy cloud-native, high-scale Big Data systems on Azure .

Posted 10/4/2026full-timeTel Aviv • IsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying cloud-native Big Data systems on Azure, with a strong focus on integrating AI/ML models for real-time insights. Proficient in optimizing data pipelines and leveraging modern technologies like Kubernetes and Kafka to build intelligence-driven products.

Highest-signal resume keywords

Big Data EngineeringCloud-Native DevelopmentAI/ML IntegrationKubernetes ExpertisePython Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonJavaScalaSpring BootFastAPIFlaskDjangoData Pipeline OptimizationDistributed Systems ArchitectureMachine Learning

Soft Skills

CollaborationProblem-Solving

Tools & Technologies

AzureAWSGCPKubernetesKafkaELKPrometheusGrafana

Certifications & Qualifications

B.Sc. in Computer Science

Industry Keywords

AI-Driven Security ToolsGenerative AISupervised LearningUnsupervised LearningModel Lifecycle

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDjangoFlaskGoogle Cloud PlatformGrafanaJavaKafkaKubernetesPrometheusPythonScalaSpringSpring BootSpringBoot

About the role

Key responsibilities & impact

Design, develop, and deploy cloud-native, high-scale Big Data systems on Azure
Optimize data pipelines
Integrate AI/ML models into production for real-time insights
Drive AI initiatives from proofs of concept to product features
Collaborate with product, UX, data science, and engineering teams
Build intelligence-driven products that help customers detect and respond to security threats
Leverage Kubernetes, Kafka, ELK, Prometheus, Grafana, and related technologies

Requirements

What you’ll need

5+ years of backend or data engineering experience, with focus on Big Data environments
B.Sc. in Computer Science or a related field
Expertise in Python, Java/Scala, Spring Boot, FastAPI, Flask, and Django
Practical expertise with Kubernetes and cloud platforms such as Azure, AWS, and GCP
Experience with large-scale data infrastructures and distributed systems architecture
Understanding of supervised and unsupervised learning, model lifecycle, and evaluation metrics
Experience with LLMs, agents, generative AI, or AI-driven security tools
Contributions to open-source projects or research initiatives in machine learning and artificial intelligence

Benefits

Comp & perks

Health, well-being, financial, and life benefits
FlexBase flexible work arrangements: work from home, in an office, or a combination of both