לוח משרות דרושים הייטק תוכנה בתל אביב יפו, לחיפוש זה נמצאו 1,199 משרות

Requirements:
What you'll own Build a qualified pipeline through outbound prospecting and timely inbound follow-up. Research target accounts and stakeholders to create relevant, thoughtful outreach. Run early discovery conversations, uncover business context, and qualify opportunities. Maintain clear CRM records and hand off sales-ready opportunities to the Sales team. Use activity, meeting, and pipeline data to improve your outreach and consistently progress toward targets.
What will help you succeed At least one year of relevant experience as a BDR, SDR, or in outbound B2B sales, with a track record of meeting sales or qualified-meeting targets. Strong spoken and written English, with the ability to sell and build rapport with prospects across the U.S., Europe, and Israel. A high level of ownership, independence, and comfort working in a fast-paced, high-expectation environment. Availability to work in our Tel Aviv hybrid model: from home on Wednesdays and Fridays, and from the office on the remaining workdays. It’s a plus if Experience with Salesforce or a comparable CRM and sales-engagement tools. Experience selling to DevOps, cloud, or other technical audiences. Strong discovery, listening, research, and follow-up skills in a high-activity environment. Why this role matters Own a business-critical pipeline-generation motion with direct visibility and impact. You will build deep B2B sales expertise while working closely with Sales leadership and introducing a technical cloud solution to engineering and cloud leaders. It is an opportunity to grow through meaningful responsibility in a team that values initiative and learning. A note on how we work We move fast, take ownership, and solve hard problems together. We value direct feedback, different perspectives, and the humility to keep learning as one team.

Requirements:
Strong hands-on experience in C/C++ software development, including system design, implementation, debugging, performance optimization, and integration of large-scale production systems.
B.Sc. or M.Sc. in Computer Science, Software Engineering, Electrical Engineering, or equivalent practical experience.
Deep understanding of Linux internals, including processes, threads, memory management, synchronization primitives, I/O subsystems, and performance troubleshooting.
Experience developing distributed systems with a focus on scalability, reliability, fault tolerance, concurrency, and high availability.
Solid understanding of networking fundamentals, including TCP/IP, routing, transport protocols, distributed communication patterns, and OSI networking layers.
Experience designing and implementing high-performance backend services operating in multi-node environments.
Strong debugging and root-cause analysis skills across complex production environments.
Experience with message brokers or event-streaming systems - advantage.
Apache Kafka internals or Kafka wire protocol experience - advantage.

Requirements:
A Builder's Mindset: You consider yourself a software engineer first, who happens to apply their skills to infrastructure reliability and complex validation.
Python Mastery: You don't just use automation tools; you build them. You write clean, scalable, object-oriented code that other engineers love to read.
Distributed Systems Context: You understand the unique pain points of Linux kernels, multi-tenant networking layers, containerization (Docker/K8s), and data pipeline architectures.
AI Curiosity: You have hands-on experience or deep curiosity regarding LLMs, prompt pipelines, and modern AI developer environments.

Requirements:
Requirments
B.Sc./B.A. degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
Good understanding of the Linux operating system.
Academic transcripts (grade sheet) - required.
Advantages
Experience with C/C++.
Experience with Python scripting.
What We're Looking For
Strong analytical and problem-solving skills.
Eagerness to learn and grow in a dynamic environment.
Excellent teamwork and communication skills.

Requirements:
Relevant academic degree (CS/ CE / EE)
At least 3 years experience in C/C++ - Must
At least 3 years as team leader - Must
Experience in design and development of enterprise-level and multi-threaded system
Knowledge and experience in Linux - Must
Experience working with Linux environments - Advantage
Experience in design, coding, integration, and debugging capabilities
Self-starter, enthusiastic proactive mindset
Ability to write code and conduct thorough code reviews.

Requirements:
A team player with strong can do mentality.

At least 5 years of experience in backend development.

Experience with micro services architecture and distributed systems.

Experience working with backend pipelines including messaging queues - Advantage.

Experience working with cloud environments - Advantage.

Experience in the healthcare tech industry (specifically EHR and HL7) - Big Advantage.

B.Sc. or higher in Computer Science or in a similar field.

Requirements:
Minimum of 6 years BE/ platform experience with proven experience as a Platform Engineer or similar role.

Knowledge of microservices architecture and distributed systems principles.

Hands-on experience with CI/CD systems such as github actions, Gitlab, Jenkins etc.

Familiarity with monitoring and logging tools (e.g., Prometheus, ELK stack) and concepts for proactive system management.

Strong communication skills and the ability to effectively communicate technical concepts with excellent problem-solving skills and ability to thrive in a fast-paced, collaborative environment.

Hands-on experience with containerization technologies (e.g., Docker, Kubernetes) and container orchestration platforms.

An autodidact that is eager to learn new technologies with a strong background in cloud infrastructure management is a big advantage.

Proficiency in high level language such as Python or similar and familiarity with bash and linux shell commands.

Requirements:
Required Qualifications:

Minimum of 10 years of hands-on experience in algorithm development using Python.

A strong foundation in software engineering principles and clean, efficient coding practices.

Extensive experience with NLP, LLMs, RAG, prompt engineering, and agentic workflows.

Experience in the deployment, delivery, and maintenance of AI algorithms in real-world production environments.

Experience in developing and deploying deep learning models (CNNs, ViTs, VLMs) for medical data classification, segmentation, and object detection tasks.

Strong interpersonal and leadership skills; a team player who can work effectively in a cross-functional environment involving product managers, clinicians, and fellow engineers.


Preferred Qualifications:

Experience with AWS.

Experience in the medical domain.

M.Sc. or higher in Computer Science or a related scientific discipline.

Requirements:
5+ years of experience as a Software Engineer, building production-grade systems.
Strong experience with backend development and building scalable services.
Proficiency in one or more modern programming languages such as Go / Python / Java / Node.js - Go adds more points, but all accepted.
Experience designing and working with distributed systems, microservices, and event-driven architectures.
Strong understanding of data structures, system design, and engineering fundamentals.
Experience working with databases (SQL) and designing data models.
Familiarity with cloud environments (AWS preferred, GCP or Azure also relevant).
Experience with Docker and Kubernetes - advantage.
Strong troubleshooting skills, ownership mindset, and ability to work independently.
Excellent communication skills and a collaborative, can-do approach.
Experience working in a fast-paced startup environment - advantage.
Background or interest in security / cloud security - strong advantage.

Requirements:
3+ years as a Team Lead across at least two workplaces, with strong leadership and people skills - clear communication and real ownership of team health. Comfortable operating independently without a dedicated PM, including direct customer communication.
6+ years as a Back-End engineer with high-scale, production data-pipeline experience - a data-engineering background is not required. Python is the primary language. able to architect solutions from scratch and deliver on time.
Startup experience is a must; enterprise experience is a plus.
Hands-on AI engineering experience: LLMs, agentic architectures, evaluation/benchmarking, prompt/context engineering.
Genuine day-to-day AI usage; comfortable owning build-vs-buy/architecture calls; shipping an AI product in production is a must.

Requirements:
8+ years of engineering experience.
2+ years of hands-on experience with proxy infrastructure.
Deep, hands-on networking expertise - TCP/UDP, sockets, HTTP/HTTPS/SOCKS5, HTTP/2/3, DNS - at the protocol level, not the surface level.
Proven experience building (not just configuring or integrating) proxy or networking infrastructure - reverse proxies, rotation systems, IP reputation and quality management.
Working knowledge of proxy types - residential, ISP, mobile, datacenter - their characteristics, trade-offs, and failure modes.
Comfortable in the Linux networking stack: iptables, routing tables, network namespaces, connection tuning.
Experience with high-throughput, low-latency, high-scale systems, and the debugging skills to chase a problem down to a packet trace when needed.
Solid cloud infrastructure skills - Kubernetes, Docker, and IaC (Terraform) - to ship and operate what you build.
A genuine AI-native mindset - daily, expert use of AI-assisted development tools to move faster without sacrificing correctness.
Strong software engineering ability in Node.js, Rust, Go, or Python - you design and build production microservices, not just scripts and runbooks.
Experience with data infrastructure at scale - high-throughput pipelines and storage (nice to have).

Requirements:
8+ years of backend software engineering experience, including end-to-end ownership of production systems at scale.
Deep expertise in Node.js and TypeScript, with strong software architecture skills for building modular, distributed systems.
Strong cloud and infrastructure experience (AWS, Kubernetes, Docker), including CI/CD, observability, reliability, and production operations.
Experience building and scaling data-intensive systems, including high-throughput data pipelines, distributed APIs, data modeling (SQL & NoSQL), and messaging platforms such as Kafka or Spark.
Experience building developer infrastructure, including internal tooling, test automation, validation frameworks, or agent-facing infrastructure (e.g., MCP servers, AI/LLM tools and APIs).
AI-native engineering mindset, with daily expert use of AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) to significantly improve engineering velocity while maintaining quality.
Technical leadership experience, including mentoring engineers, driving architecture decisions, and raising engineering standards across a team.
Experience working in fast-paced startup or scale-up environments, delivering for customers under short SLAs.