דרושים » תוכנה » Cloud DevOps Engineer

Requirements:
Full proficiency in AWS and Linux environments.
Minimum 2 years of experience in cloud and system operations.
Basic to intermediate scripting skills (Bash, Python, or PowerShell).
Experience with firewall configuration and system security.
Strong analytical and troubleshooting skills.
Experience with performance profiling or monitoring tools.
Ability to write production-level code (e.g., in Java, Python, or similar).
Familiarity with MySQL.

Requirements:
What You Bring
Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related engineering discipline, or equivalent practical experience.
5+ years of professional software engineering experience, including substantial experience building backend systems, distributed systems, or data-intensive applications in production environments.
Strong Python engineering skills, including modular architecture, dependency management, testing practices, observability, and production-grade code quality.
Strong SQL and data modeling expertise, including schema design, indexing strategies, event-driven data models, and scalable analytical aggregations.
Hands-on experience building incremental and idempotent data pipelines that handle duplicate, invalid, and late-arriving events without impacting downstream consumers.
Experience with at least one major cloud platform (Azure, GCP, or AWS) and modern lakehouse technologies such as Databricks, Delta Lake, Spark, or equivalent architectures.
Experience with streaming or messaging technologies such as Kafka, Pub/Sub, Event Hubs, or similar event-driven systems.
Proven ability to diagnose and resolve production data issues, including data quality problems, schema evolution, backfills, replay scenarios, and performance bottlenecks.
Strong written and verbal communication skills in English and experience collaborating effectively with globally distributed teams.

Nice to Have
Experience building industrial, IoT, manufacturing, or operational data platforms.
Familiarity with Digital Twin architectures and industrial data models.
Experience with graph databases, context graphs, knowledge graphs, or relationship-centric data modeling.
Exposure to AI/LLM-powered applications, including retrieval-augmented generation (RAG), agents, tool calling, or evaluation frameworks.
Experience working with Databricks or similar lakehouse platforms from both application and platform perspectives.
Experience building data products that directly support AI agents, intelligent applications, or machine learning workflows.

Requirements:
What You Bring
5+ years of professional software engineering, MLOps, or ML platform engineering experience in production environments.
Significant experience building or owning production ML infrastructure and lifecycle systems.
Strong Python engineering skills with production-grade architecture, modular design, testing, packaging, and robust error handling.
Strong understanding of the end-to-end ML lifecycle including training, deployment, monitoring, retraining, reproducibility, and lineage.
Experience working with large-scale data platforms such as Databricks, Spark, Delta Lake, or equivalent ecosystems.
Experience with ML platform and MLOps frameworks such as MLflow, Metaflow, Kubeflow, or equivalent ML lifecycle-management systems.
Proven ability to design reusable workflow orchestration using Airflow, Metaflow, or Databricks, covering automation, scheduling, dependency management, and production reliability.
Familiarity with operational patterns for LLMOps, AgentOps, and production AI systems.
Strong written and verbal communication skills in English.

Nice to Have
Experience with industrial, IoT or manufacturing platforms.
Experience with feature stores, model registries, dataset versioning, and lineage systems.
Experience with AI agents, RAG systems, production GenAI applications, or evaluation frameworks.

Requirements:
3-6 years of building SaaS applications, preferably in a service-oriented architecture
Bachelors Degree in Computer Science, Software Engineering, or equivalent.
Expertise in modern web development frameworks, C#, Java, or equivalent.
Experience in writing optimized SQL and working against various different datastores.
Demonstrated success with scalable web applications or messaging systems
Experience with web security is a plus.

Requirements:
* 7+ years of experience as a Systems Engineer, Infrastructure Architect, or IT Architect within enterprise environments.
* Proven experience leading large-scale technology projects and complex infrastructure initiatives.
* Strong expertise in systems engineering and enterprise architecture methodologies.
* Extensive experience writing architecture, design, and technical documentation, including HLD and LLD documents.
* Deep knowledge of enterprise IT infrastructure, including compute, networking, cybersecurity, cloud, and disaster recovery solutions.
* Strong understanding of Storage, operating systems, virtualization technologies, and modern data platforms.
* Excellent analytical and troubleshooting capabilities in complex distributed environments.
* Strong communication skills and the ability to work effectively with technical teams and senior stakeholders. Advantages
* Experience designing hybrid cloud environments across on-premises and public cloud platforms.
* Experience with enterprise networking architecture and IP-based communication infrastructures.
* Familiarity with advanced cybersecurity and information security solutions.
* Relevant industry certifications in cloud, networking, architecture, or cybersecurity.
* Background in technology-focused military units.
* Experience leading enterprise transformation and modernization initiatives.

Requirements:
You Will Bring
6+ years of professional software engineering experience.
Strong Python development skills.
Strong backend engineering background, including APIs, services, integrations, or microservices.
Proven experience designing, shipping, or operating LLM-powered applications or GenAI systems.
Experience with RAG, AI agents, tool/function calling, prompt orchestration, evaluation, and observability.
Experience with microservices, distributed systems, and production backend architecture.
Strong understanding of system design, reliability, security, scalability, latency, and maintainability.
Ability to work with complex data models and expose them safely through AI systems.
Ability to operate in ambiguous technical areas and turn prototypes into production-ready systems.
Strong communication skills and ability to explain technical decisions clearly.

Preferred Qualifications
Experience with LangChain, LangGraph, or LangSmith.
Experience with Go, MongoDB, Databricks, Kubernetes, Docker, REST APIs, vector search, or event-driven systems.
Experience with Azure OpenAI, Gemini, or similar LLM platforms.
Experience building or using knowledge graphs, GraphRAG, or graph databases such as Neo4j.
Experience building multi-agent systems or orchestrating multiple specialized agents/tools in production.
Experience building internal platforms, SDKs, developer tools, or shared engineering infrastructure.
Experience with authorization, data segregation, multi-tenant systems, or user-level data scoping.
Experience in industrial, IoT, predictive maintenance, manufacturing, or operational-data domains.

Requirements:
Minimum qualifications:
Bachelors degree or equivalent practical experience.
4 years of experience building developer tools that improve developer velocity, code quality, and code health (e.g., compilers, automated).
4 years of experience with software development in one or more programming languages, and with data structures and algorithms.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Preferred qualifications:
3 years of industry experience with high performance, large-scale systems, and debugging.
Experience in chip design and related EDA tools and flows.
Deep understanding of object oriented programming and functional programming.
Proficiency in code and system health, diagnosis and resolution, and software test engineering.
Ability to write and understand SystemVerilog register transfer level (RTL) code.
Excellent software skills and design practices.

Requirements:
BSc in Software Engineering, Computer Science, or a related field.
3+ years of experience in software development.
Excellent control of CI tools - Jenkins, Gitlab /Github, Git, Repo, ks8 services.
Excellent Python programming skills.
Experience in Linux and bash scripts.
Passion for problem-solving and debug capabilities
Team player with strong communication skills, able to mentor others and lead technical discussions.
Independent, proactive, and quick to learn, with a creative mindset for solving complex challenges.

Requirements:
Basic Qualifications
- Bachelors (or higher) Degree in Computer Science (CS), Electrical Engineering (EE) or related area.
- 8+/10+ years of programming with at least one software programming language experience.

Preferred Qualifications
- Experience as a mentor, tech lead or leading an engineering team.
- Experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
- Data-center Networking.
- Network related simulators.
- Large-scale distributed environments.
- Storage and/or Transport protocols.
- Real-Time development.

Requirements:
M.Sc., or Ph.D. in Electrical Engineering, Computer Science, Physics, Mathematics, or a related field.
4+ years of experience in ML applications, including research on time-series data, ML-based vectoring, and Embeddings (as Transformers, TGNN, TSFM, Graph Transformer, GNN, CNN, etc.)
Proficiency in Python (Pytorch, Pandas, NumPy, PyG - nice to have), and Applied Science SDLC - Discovery, Research, development, fidelity, deployment, monitoring, Training, and fine-tuning
Experience in anomaly detection, abnormal behavior, outliers, pushing recall, precision, and tail metrics KPIs boundaries
Experience working with ML infrastructure such as MLFlow, Vertex AI, Sagemaker etc.
The ability to translate research into scalable, production-ready solutions.
Experience working on Agile teams with a passion for fast iterations, feedback, and continuous learning.
Proven ability to collaborate with diverse, cross-functional groups, including product managers, infrastructure, and data engineering teams.
Experience in feature engineering-based signal processing - a big advantage.