דרושים » הנדסה » Senior Backend Engineer

Requirements:
5+ years of software engineering experience, with at least 2 years in Python.
Experience building back-end services using microservices architecture.
Proficiency with both SQL and NoSQL databases.
Strong background in designing scalable, distributed systems.
Hands-on experience in CI/CD environments and modern testing frameworks.
Solid understanding of TDD and a quality-first engineering mindset.
Excellent communication skills in English.
🌟 Bonus Points For:
B.Sc. in Computer Science, Engineering, or equivalent experience.
Startup experience or work in multidisciplinary tech environments.
Experience with multi-threaded or multi-tasked applications.
Hands-on with AWS (e.g., Lambda, SQS, CloudFront, EKS).
Familiarity with Docker, Kubernetes, and RESTful services.
Exposure to computer vision or AI-driven systems.
Background in video systems (streaming, encoding, media servers).
Experience with any of our stack: GitLab, InfluxDB, RabbitMQ, MongoDB, PyTorch.

Requirements:
B.Sc. in Computer Science or equivalent.
8+ years of hands-on software development experience (preferably in startups).
4+ years leading engineering teams.
Deep experience in backend tech: Python, Docker, Kubernetes, SQL/NoSQL databases, message queues.
Strong grasp of scalable system architecture and multi-threaded development.
Cloud-native experience with AWS.
Strong testing mindset and CI/CD familiarity.
Excellent communication skills in English.
Nice-to-haves:
Experience in computer vision or AI-driven products.
Video systems background (e.g., streaming, encoding).
Exposure to GitLab, InfluxDB, RabbitMQ, MongoDB, PyTorch, AWS services (SQS, Lambda, CloudFront, EKS).

Requirements:
Required Skills & Qualifications
Experience: 5+ years of professional software development experience.
Programming Languages: Proficiency in one or more languages such as C#, JavaScript/TypeScript, or Go.
Frameworks & Technologies: Experience with frameworks such as .NET Core & React.
Databases: Strong understanding of relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) databases.
Microservices & APIs: Strong experience in building RESTful APIs and microservices architectures.
Data Lakes & Warehouses (Advantage): Experience working with one of the leading vendors for big data processing, analytics, and storage.
Cloud Platforms (Advantage): Experience with AWS, Azure, or Google Cloud Platform (GCP).
Security & Compliance (Advantage): Understanding of secure coding practices and data protection regulations.
Testing (Advantage): Experience with unit testing, integration testing, and automated testing frameworks.
CI/CD & DevOps (Advantage): Experience with Docker, Kubernetes, Gitlab, or other CI/CD tools.
Education (Advantage): Bachelors or Masters degree in Computer Science, Software Engineering, or relevant army training.
Preferred Skills & Qualifications
Experience working with one of the leading Data Lake & Warehouse vendors for big data processing, analytics, and storage.
Experience with any of the leading cloud platforms AWS, Azure, or Google Cloud Platform (GCP).
Understanding of secure coding practices and data protection regulations.
Experience with unit testing, integration testing, and automated testing frameworks.
Experience with Docker, Kubernetes, Gitlab, or other CI/CD tools.
Experience in distributed systems, event-driven architecture, or message queues (Kafka, RabbitMQ).
Knowledge of front-end development (React, Vue.js, or Angular).
Bachelors or Masters degree in Computer Science, Software Engineering, or relevant army training.
Contributions to open-source projects or personal coding projects.
Familiarity with observability and monitoring tools like Prometheus, Grafana, or Datadog.
Soft Skills
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, Agile development environment.
Passion for continuous learning and staying updated with industry trends.
Additional Skills:
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, Solutions Design, Testing & Automation, User Experience (UX).

Requirements:
Youre a seasoned Backend Tech Lead with a deep passion for backend systems and strong leadership qualities. Heres what were looking for:
Strong proficiency in Python: Extensive experience with Python and web frameworks in a production environment.
Leadership experience: Proven ability to lead, mentor, and inspire engineering teams.
Backend expertise: Experience with building, deploying, and optimizing large-scale backend systems using databases like MySQL, and NoSQL systems (e.g., Redis, Elasticsearch).
Cloud platforms: Expertise in cloud infrastructure and services for backend service deployment and management.
Microservices and APIs: Solid experience designing and implementing backend APIs and microservices architectures that are modular, scalable and maintainable.
Containerization and orchestration: Familiarity with Docker and Kubernetes for containerized applications and orchestration.
High-performance systems: Ability to identify performance bottlenecks and optimize backend systems to handle large-scale traffic with minimal latency.
Strong communication skills: Excellent verbal and written communication skills, with the ability to explain complex technical concepts.

Desired Skills:
- Experience: At least 5 years of solid backend engineering experience, with at least 2 years in a leadership or tech lead position.
- Education: A degree in Computer Science
Collaborative mindset: A passion for working in a team-oriented environment and helping others grow technically.

Requirements:
Minimum Qualifications:
Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering, or a related field from a leading university, or equivalent experience accepted in lieu of degree.
2+ years of professional software engineering experience.
Full proficiency in Python (Go advantage).
Experience with deploying and managing containerized applications using orchestration platforms (Kubernetes, Docker).
Experience with cloud infrastructure platforms (AWS - advantage) and with Linux environments.

Preferred Qualifications:
Experience with event-driven architecture and event processing services, including streaming platforms and message brokers (Kafka, Kinesis, RabbitMQ, Redis).
Experience in modern ETL/ELT frameworks (Airflow, Spark, dbt, Snowflake, AWS Glue) for building scalable data pipelines. Hands-on experience with monitoring tools (Prometheus, Grafana, Datadog), observability platforms (Elasticsearch, Logstash, Kibana, Splunk), and data management systems (OpenMetadata, Datahub, Great Expectations).
Hands-on experience in version control (Git) and CI/CD pipelines (Github Actions, Jenkins) for deploying and maintaining data infrastructure.
Strong advantage - Familiarity with Large Language Models (LLMs) and AI/ML integration in data systems, including familiarity with vector databases model embeddings.

Requirements:
6+ years of professional experience as a software engineer with a strong emphasis on backend development in both dynamic and statically typed languages preferably Java.
A solid understanding of distributed and scalable production systems.
High standards for code quality, testability, maintainability, security and performance.
Experience with monitoring and troubleshooting live-production applications a must.
Experience with relational and non-relational databases (MySQL, Redis, DynamoDB).
Experience with OOP, TDD and MVC.
Previous experience with NodeJS an advantage.
Previous experience working on Travel systems, online booking tools, GDS systems and/financials and payments systems an advantage.
Experience in a startup environment an advantage.
Team player with excellent communication and collaboration skills.
Fluent English spoken and written.

Requirements:
5+ years of professional experience as a backend developer, with strong skills in Python
Solid experience in developing services on cloud platforms, particularly AWS (experience with Azure or GCP is a plus).
Expertise in Python frameworks and Node.js frameworks (e.g., Express).
Strong understanding of software engineering principles, including system design and data structures.
Experience building RESTful APIs and microservices architectures.
Familiarity with relational and NoSQL databases (e.g., MySQL, MongoDB).
Strong debugging, performance optimization, and troubleshooting skills.
Strong communication and collaboration skills, with the ability to work effectively in a team.
Proactive, detail-oriented, and self-motivated with the ability to thrive in a fast-paced environment.
Nice-to-Have:
Experience with Node.js
Knowledge of serverless architecture (e.g., AWS Lambda).
Experience with DevOps tools and practices, including:
Infrastructure as Code (IaC) tools like Terraform.
Containerization and orchestration tools like Docker and Kubernetes (K8s).
CI/CD tools such as Jenkins or similar.
Knowledge of security best practices for cloud-based environments.
Previous experience working in an infrastructure or architecture team.

Requirements:
BSc in Computer Science or a related field.
6+ years of experience building and deploying ML systems in production environments.
Proficiency in Python and production frameworks like FastAPI, Databricks, SageMaker, and MLflow.
Proven track record in deploying and maintaining ML/LLM services (APIs, microservices, serverless, or containerized).
Strong understanding of software engineering fundamentals: object-oriented design, testing, version control, CI/CD, and performance optimization.
Experience working with agentic workflows or LLM-based agents.
Ability to work independently and break down complex, ambiguous problems into structured solutions.
Strong communication skillsable to explain technical concepts to both technical and non-technical stakeholders.
Advantages:
Hands-on experience with Kubernetes, Airflow, Spark, ArgoCD, and Docker.
Experience working with databases such as Elasticsearch, vector databases, PostgreSQL, and SQL.
Experience fine-tuning or integrating open-source LLMs in production environments (e.g., RAG, LoRA, agent frameworks).
Contributions to open-source ML or MLOps projects.

Requirements:
6+ years of backend development experience, ideally in platform engineering.
Proficiency in backend languages such as Go, Python, or Node.js.
Experience with cloud platforms (AWS, GCP, or Azure).
Hands-on experience with Docker, Kubernetes, and microservices orchestration.
Familiarity with Infrastructure-as-Code tools (Terraform, Helm).
Knowledge of cloud security best practices and compliance standards.
Strong analytical and problem-solving skills; self-starter attitude.
Experience working with both SQL (PostgreSQL, MySQL) and NoSQL databases.
Nice to Have:
Experience with observability tools (Prometheus, OpenTelemetry, Coralogix, etc.).
Understanding of cloud cost optimization techniques.