דרושים » מחשבים ורשתות » Senior Software Engineer (DevOps)

Requirements:
What you have:
3-5 years of hands-on experience in DevOps, Platform Engineering, or Infrastructure Engineering roles.
Strong hands-on experience working with AWS in production environments.
Proven experience with AWS services such as EKS, EC2, IAM, VPC, Route 53, S3, RDS, Lambda, CloudWatch, or similar services.
Strong experience with Kubernetes and containerized environments.
Hands-on experience with Infrastructure as Code tools, preferably Terraform.
Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Argo CD, or similar technologies.
Experience writing automation or production-grade code using Python, Go, Bash, or a similar language.
Strong understanding of Linux, networking, DNS, load balancing, and distributed systems.
Experience with monitoring, logging, tracing, and observability platforms.
Strong troubleshooting skills and the ability to investigate complex production issues.
Ability to work independently, take ownership, and drive projects from design through production.
Strong English communication skills and the ability to collaborate across multiple engineering teams.

AI Experience you have:
Hands-on experience using AI and Generative AI tools as part of software development, infrastructure, or operational workflows.
Experience working with LLM APIs, AI coding assistants, or AI automation tools.
Ability to identify processes that can be improved through AI and translate them into practical engineering solutions.
Understanding of prompt engineering, responsible AI usage, and the secure handling of sensitive information.
Experience with CAG, AI agents, RAG, MCP, LLM integrations, or AIOps solutions is an advantage.

Bonus points:
Experience working with data platforms, data infrastructure, or large-scale data processing systems.
Understanding of data pipelines, data ingestion, streaming systems, or distributed data architectures.
Experience operating large-scale, multi-region, or multi-account AWS environments.
Experience with GitOps tools such as Argo CD or Akuity.
Experience with service mesh, API gateways, or service discovery solutions.
Experience with Datadog, Prometheus, Grafana, OpenTelemetry, or similar observability tools.
Experience with cloud security, secrets management, and Vault.

Requirements:
Bachelor's degree in Computer Science, Software Engineering, or a related field - an advantage. 3+ years of hands-on experience in DevOps engineering, building and maintaining production environments. 3+ years of hands-on AWS experience, including services such as EC2, S3, RDS, ECS/ECR, EKS, Lambda, IAM, and VPC. Hands-on experience using Generative AI tools (e.g., GitHub Copilot, Claude Code, Cursor, or similar) as part of day-to-day engineering workflows, including scripting, automation, troubleshooting, and infrastructure configuration. Experience with GCP - an advantage Strong hands-on experience with Terraform and Terragrunt - a must. Hands-on experience with Ansible – an advantage. 2+ years of hands-on Python experience, with the ability to develop scripts and tools for automation, monitoring, and infrastructure management. Strong understanding of networking concepts, including TCP/IP, HTTP/HTTPS, proxies, DNS, load balancing, and VPNs. Hands-on experience with Docker and Kubernetes, including deploying and troubleshooting containerized workloads. Hands-on experience building and maintaining CI/CD pipelines using CircleCI, Bitbucket Pipelines, or equivalent tools; CircleCI experience is preferred. Strong Linux administration and troubleshooting skills, including performance, networking, permissions, and security. Excellent troubleshooting, problem-solving, and analytical skills. Strong communication skills and the ability to work both independently and collaboratively. Fluent English, both written and verbal Fast learner with a broad technical mindset and strong team-player attitude. Can-do attitude with a proactive, ownership-driven approach to problem-solving.

Requirements:
7+ years of experience in DevOps, with a proven track record as a lead or founding engineer in an early-stage startup
The "0 to 1" Skillset: Experience building infrastructure from scratch
Cloud & Container Mastery: Deep proficiency with AWS (specifically ECS or EKS), Terraform/Pulumi, and Docker
Observability Expert: Experience building self-hosted monitoring and logging stacks that do not rely on third-party SaaS (Prometheus/Grafana is a must)
Networking Depth: Strong understanding of Linux networking (L3-L7), secure tunneling, and VPC configurations
Independent Builder: Ability to make high-level architectural decisions autonomously and execute them with minimal supervision
Proficiency in Python for building custom automation tools

Requirements:
At least 10 years software development experience, at least 2 years of experience as architect
Understands system engineering and architecture, proven experience in scale, system redundancy solutions, and performance
Experience in high-capacity and high-reliability products in multiple development languages and environments, multi-threading, and more
Experience with SQL Server
Understands Microservice, and event-based design and SAGA concepts
Error tolerance and zero data loss concepts
Experience delivering systems operated globally
Meaningful hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) - architecting and operating production workloads at scale
Experience architecting AI-enabled systems - LLM integration patterns, RAG, agentic/multi-step workflows, evals, and production concerns specific to AI (latency, cost, fallback, hallucination control)
AI fluent - daily, hands-on use of AI coding tools with clear judgment on when to trust output vs. rewrite it; goes beyond using AI to configuring it (custom instructions, rules, MCPs, tools); builds workflows and skills, not just prompts
Strong attention to business needs and converting them into working, effective products
Ability to adapt to various technologies and research new concepts
A true team player, able to both hold and drive a vision - and also to buy into it
Proactive attitude and does what it takes to get things done
Connected and updated in the latest & greatest of technology
A passion for technology!

Requirements:
Significant experience in managing the delivery/installation of technical solutions - minimum of 5 years.
Strong technical background with experience working directly with server rooms, and network installations.
Experience working with hardware-based systems.
Deep understanding of networking and the ability to troubleshoot and resolve complex network issues.
Experience in creating technical documents, presentations, and explaining technical processes to various audiences.
Excellent English communication skills - both written and spoken.
Ability to work under pressure and manage multiple projects simultaneously.
Hands-on approach and deep technical understanding - initial phase of the role will involve performing installations personally.

Requirements:
At least 7 years of experience as a backend engineer
Experience shipping production AI systems - running them in the real world and fixing what breaks, not just building them
Understanding of agentic architectures - orchestration, multi-step workflows, fallback and error logic
Strong eval instincts - you define metrics, build test sets, and dont ship until you can measure
Full-stack range - comfortable across the prompt, RAG pipeline, orchestrator, and backend
Comfortable across any stack - you go where the right solution is
Honest communication - you flag problems early and give direct, candid feedback
You understand production concerns such as reliability, maintainability, security, observability, latency, and cost.
AI fluency 
Real fluency with AI coding tools - genuinely fast, not just "familiar with"
Think in workflows, not endpoints - agentic loops, skills, and orchestrated flows; CRUD with an LLM bolted on isnt a system
Clear judgment about when to trust AI output and when to rewrite it
Goes beyond using AI - builds skills, workflows, and harnesses, not just prompts
You understand common AI-system risks such as hallucinations, prompt injection, data leakage, unreliable tool execution, and uncontrolled autonomy.
Good to have :
Fintech or regulated-environment experience - understanding why "probably fine" isnt acceptable when money is moving

Requirements:
5+ years of experience in AI/ML engineering or applied data science with production engineering responsibilities
Strong Python skills and solid software fundamentals
Experience building production LLM-powered systems, including prompt design, embeddings, fine-tuning, RAG; agent experience is a plus
Solid ML foundations; NLP, document AI, or multimodal experience is a plus
Hands-on experience with modern AI tooling (Hugging Face, PyTorch, LangChain, LangGraph) and cloud infrastructure (AWS preferred)
Strong communication and collaboration skills; comfortable working cross-functionally with product and domain teams
BS/MS/PhD in Computer Science, Data Science, or Engineering (MS/PhD a plus).

Requirements:
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
Experience in software development, with a strong emphasis on object-oriented programming and design patterns.
Proficiency in programming languages C and C++
Solid understanding of data structures, algorithms, and distributed systems.
Strong problem-solving skills and the ability to work independently and as part of a team.
Capable of delivering on multiple competing priorities with little supervision
Strong technical skills and enthusiasm to learn new technologies
Software Testing and Debugging
Good verbal and written communication skills in English

Requirements:
5+ years of relevant industry experience as a software engineer
Experience in OS Internals such as Linux/Android/Windows and system-level programming
Proficiency in software security
Substantial experience building complex software systems
Mastering software development processes and methodologies
B.Sc. in Computer Science or Software Engineering or Equivalent military experience courses in elite intelligence corps.
Advantages:
Experience in Objective-C or Swift using iOS or OS X frameworks - a major advantage
Experience developing in Apple's ecosystem (macOS/Xcode)
Experience in JavaScript - a major advantage
Hands-on experience with Python
Knowledge of reverse engineering techniques and tools (e.g., IDA Pro).

Requirements:
We care about a particular mindset more than any specific item on a checklist. The person who'll thrive here is someone already living inside the modern AI stack - not planning to start. You read model release notes the way other people read the news. You've built real things with new tools the week they came out. Agentic dev workflows aren't something you've heard about; they're how you already work. When a new model drops, your first instinct is to put it on the bench. And underneath all of it, you're a builder - you ship, you write clean software, and you think about latency, cost, and what the user actually needs.

What We're Looking For

6+ years of software engineering experience, with the last few focused on AI / ML systems
Deep, hands-on experience designing and shipping agent systems in production - not demos. You understand agent architectures, memory, tool use, evaluation, and the failure modes that matter at scale.
Strong fundamentals in embeddings, RAG, and hybrid retrieval, with real experience designing vector storage and retrieval pipelines for production use
Deep production backend foundations - strong Postgres knowledge (functions, triggers, indexes, extensions, atomic operations, and similar depth), real-time client channels (WebSockets, SSE), async and event-driven backbones (pub/sub, queues, background tasks, webhooks), the ability to design systems and features around multithreading and multiprocessing, and dynamic resource management for high-throughput, latency-sensitive workloads.
Excellent architecture instincts and strong Python - you write code that scales and that other engineers can build on
Product sensibility - you can reason about trade-offs and what's worth building, not just what's technically possible