לוח משרות דרושים הייטק AI משרה מלאה, לחיפוש זה נמצאו 277 משרות

Requirements:
Requirements are often considered a measure of how equipped you are to do the job, but sometimes they arent the only factor.
If you dont have every skill listed here but believe youd be a great fit, wed still love to hear from you!
5+ years of experience as a software engineer with a strong emphasis on backend development.
Excellent knowledge of software design, clean architecture, and scalable distributed systems.
Proven experience in leading end-to-end feature development - from design through implementation, testing, and deployment.
Solid experience with testing methodologies (unit testing, TDD, mocking, etc.).
Proficiency with relational databases (PostgreSQL, MySQL, etc.).
Experience with LLMs in production is a strong advantage.
Experience with cloud platforms (AWS or equivalent) is a plus.
Independent, fast learner, and passionate about exploring new technologies.
Proactive team player with a desire to impact our team, our product, and our customers.
Research-based masters degree in Computer Science, Data Science, Statistics, or a related field
Previous professional experience in Data Science and hands-on data analysis, with the ability to investigate
complex datasets, test hypotheses, and translate findings into engineering decisions
Ability to independently research and evaluate new tools, technologies, and platforms, build proofs of concept, and drive their integration into production systems

Requirements:
6+ years of product management experience in B2B SaaS or platform-oriented environments
Experience working on AI-powered products, preferably including GenAI
Good technical understanding and ability to work closely with engineers on complex systems
Familiarity with concepts such as LLMs, retrieval, or data-driven systems (hands-on experience is a plus)
Strong product thinking, ability to balance user needs, business goals, and technical constraints
Experience working with data, metrics, and experimentation
Ability to work across teams and drive alignment in ambiguous environments
Strong communication skills and ability to clearly articulate product decisions
Strong advantage
Experience building platform products, APIs, or internal tools
Familiarity with AI evaluation, monitoring, or experimentation frameworks
Background in technical roles (engineering, data, etc.)
Experience in domains requiring high trust and reliability (e.g., HR, finance, security)
How to evaluate if this role fits you
You might be a strong fit if:
You enjoy working on systems and platforms, not only end-user features
You are curious about how AI systems work under the hood and want to deepen that understanding
You are comfortable collaborating closely with engineers and learning technical concepts
You like solving problems that impact multiple teams and products
This role can fit candidates coming from different backgrounds, what matters most is your ability to grow into the space, take ownership, and contribute to building a scalable AI platform.

Requirements:
Requirements are often considered a measure of how equipped you are to do the job, but sometimes they arent the only factor. If you dont have all the skills, wed still like to hear from you. This could be the perfect fit for you and us.
5+ years of experience in DevOps, Platform Engineering, SRE, or similar infrastructure-focused roles
Strong coding experience in Python, Go is an advantage
Hands-on experience building or operating production LLM applications and agentic workflows
Experience with LangGraph, LangChain, Supervisor, or similar frameworks
Experience building AI SDLC platforms or harnesses that support the full lifecycle of AI-assisted software delivery
Experience with AI observability and evaluation, preferably Langfuse, OpenTelemetry, and LLM-as-a-judge approaches
Experience with AWS, Kubernetes, Helm, and GitOps CI/CD tools such as GitHub Actions and ArgoCD
Experience building internal developer platforms, DevEx tooling, or engineering automation
Strong ownership, problem-solving skills, and ability to lead cross-team initiatives
Nice to have
Experience with RAG, knowledge bases, MCP, tool calling, and AI guardrails
Experience with Terraform/OpenTofu, Crossplane, and the wider Argo ecosystem
Experience with Datadog, Prometheus, service mesh technologies, or large-scale distributed systems.

Requirements:
what we need to see:
we are looking for individuals who demonstrate a strong foundation in deep learning and a proven ability to translate innovative ideas into practical, scalable systems.
phd in Machine Learning, Computer Science, engineering, or a related discipline.
8+ years of hands-on experience in developing, training, and deploying deep learning models at scale, including llms, transformers, ssms, and/or generative models.
experience with multimodal learning and integrating diverse data modalities is highly valued.
experience with agentic ai frameworks or systems (e.g., tool-augmented models, planning-based agents, or multi-agent systems) is a strong advantage.
strong expertise in distributed training, optimization, and inference.
proven ability to lead independent research, implement robust solutions, and rigorously evaluate performance.
track record of publications and presentations at top conferences.
strong programming skills in Python and C ++, with experience in pytorch and/or cuda.
excellent communication skills and ability to thrive in a dynamic, research-driven team. mentoring experience is a plus.
ways to stand out from the crowd:
hands-on experience building advanced ai systems, including agentic ai (rag, tools, planning, multi-agent) and multimodal models combining vision, language, and structured/time-series data.
proven track record optimizing large-scale ml systems, with experience in data pipelines and distributed frameworks for llm-scale data.

Requirements:
what we need to see:
bachelor's degree in Computer Science or related field, or equivalent experience
minimum 5+ years of experience operating and supporting large-scale Linux -based compute infrastructure
develop, fine-tune, and deploy advanced llm-based solutions for [specific applications, e.g., NLP, chatbots, content generation, or data analysis
strong hands-on experience supporting and tuning job scheduling systems (lsf, slurm, etc.) in hpc or silicon design environments
proficiency in Linux systems administration (centos/rhel)
proficient in modern ci/cd techniques, gitops and infrastructure as code(iac)
proficient in Python programming and bash scripting
ways to stand out from the crowd:
deep knowledge of job scheduling systems (lsf, slurm, etc.) configuration tuning, scheduler internals, and advanced troubleshooting techniques
network licenses (e.g. flexlm) continuous maintenance, provisioning, automation, monitoring and troubleshooting
experience implementing reliability engineering practices within hpc scheduling environments
experience building or enhancing observability systems, including metrics collection, monitoring pipelines, alerting strategies, and performance dashboards
background with container technologies such as docker, singularity, or podman in hpc environments

Requirements:
what we need to see:
b.sc. in Computer Science, software engineering, or a related field, or equivalent experience.
3+ years of software development experience.
strong Python skills. you build well-structured systems, not just scripts.
hands-on experience building applications with llms, such as agents, tool use, or rag.
strong problem-solving skills and the ability to take a feature from idea to production.
excellent verbal and written english. we are a multi-language team that works across sites and time zones.
ways to stand out from the crowd:
experience evaluating the quality of llm-based systems.
knowledge of the Linux Kernel, networking, or device drivers.
experience with TEST automation or verification.
Full Stack or DevOps experience.
a track record of ai tools that real users adopted.
we are committed to fostering a diverse work environment and proud to be an equal opportunity employer. as we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements:
m.sc. or ph.d. in Computer Science, electrical engineering, computer engineering, or equivalent experience
20+ years of industry experience in systems design, distributed systems, system software, or related fields
chief Scientist, CTO, or equivalent senior technical leadership experience in smaller companies is highly desirable
deep background in distributed systems, parallel computation, networking, Storage, virtualization, and memory management
experience building, scaling, and supporting environments for massive ai workloads
strong understanding of large-scale systems operational aspects, including performance, reliability, scalability, and supportability
excellent communication, collaboration, and technical leadership skills in a multi-national, multi-time-zone environment
ways to stand out from the crowd:
proven research track record in ai systems, large-scale infrastructure, or advanced systems co-design
deep expertise in gpu systems, rdma, nvlink, and Storage technologies for ai and hpc workloads
strong record of cross-functional influence spanning hardware, system software, networking, and infrastructure
we are widely considered to be one of the technology world's most desirable employers. we have some of the most forward-thinking and hardworking people in the world working for us. if you're creative, autonomous, and excited to drive the future of ai infrastructure at scale,

Requirements:
:Key Responsibilities Information Systems Management Own and manage the company's internal business systems, SaaS platforms, and operational tools. Lead the implementation, configuration, integration, and continuous improvement of business applications. Ensure system reliability, user access management, data integrity, and operational excellence. Partner with internal stakeholders and external vendors to align systems with evolving business needs. Identify opportunities to simplify technology stacks, enhance data quality, and improve system efficiency. AI & Business Process Automation Drive the organization's AI and automation strategy by identifying high-impact opportunities across business functions. Design, build, and maintain automated workflows using platforms such as n8n, Make, Zapier, or similar tools. Implement AI-powered solutions using leading LLM technologies including OpenAI, Claude, and related AI platforms. Develop intelligent agents, assistants, and workflow automations to support business operations. Integrate business systems through APIs, webhooks, and automation frameworks. Automate repetitive and manual processes across departments including Operations, Finance, HR, Customer Success, and Sales. Monitor, measure, and optimize automation initiatives based on efficiency gains, cost savings, quality improvements, and business impact. Systems Integration & data Management Build and maintain integrations across internal and external platforms using APIs and modern integration technologies. Work with structured and unstructured data to support automation and AI-driven initiatives. Ensure proper governance, security, privacy, and compliance standards are maintained across systems and AI implementations. Troubleshoot and continuously improve system integrations and workflow reliability. Maintain clear documentation of system architecture, integrations, and automation processes. Business Partnership & Project Leadership Collaborate directly with business leaders to understand challenges, define requirements, and identify improvement opportunities. Translate business needs into scalable technical solutions. Lead technology and automation projects end-to-end, from discovery and design through implementation, testing, deployment, and support. Help drive AI adoption across the organization by enabling teams and promoting best practices. Remain up to date with emerging technologies, AI capabilities, automation tools, and industry trends.

Requirements:
What we're looking for
A bachelor's in Computer Science or equivalent, plus at least 3 years building software in production - strong fundamentals, proven track record.
Obsessed with agents and LLMs. You've built something real with OpenAI, Anthropic, or open models - shipped at work or on your own - not just read about them.
You think in planning loops, tool selection, memory, and reliability, not prompt-in / text-out.
Strong Python, comfortable in async/await, and you reason about error handling, edge cases, and what happens when a model call fails.
AI-native in how you work: Cursor, Claude Code, Copilot daily - and you understand every line you ship, not just the ones you typed.
A fast learner who dives into unfamiliar code, reads the source, and asks sharp questions instead of waiting to be unblocked.
You take an architecture you didn't design, extend it, and stress-test it - comfortable implementing patterns rather than setting them, for now.
Nice to have:
You've shipped multi-step LLM pipelines or RAG before.
You know FastAPI, async Python, PostgreSQL and SQLAlchemy, or message queues.
You've worked in sales tech or RevOps.
You've contributed to an open-source AI or agent project.

Requirements:
7+ years of software engineering experience in tech-first product companies or high-growth startups
AI-pilled daily workflow: You use AI coding tools as your primary workspace, leveraging AI across the full software lifecycle (planning/design, implementation, testing, refactoring, maintenance) while maintaining high standards for architecture, quality, security, scalability, and reliability
Hands-on with agents in production: tool calling, context management, evals, and cost and latency tradeoffs.

Requirements:
6+ years of product management experience in B2B/B2B2C SaaS.
Proven, hands-on experience shipping AI-powered features in production, ideally LLM-based agents or agentic workflows that take action, not just generate content.
A strong working understanding of the modern AI stack: LLM capabilities and limitations, prompt and context engineering, RAG, tool/function calling, evaluation frameworks, and cost/latency tradeoffs.
Experience designing human-in-the-loop experiences and building user trust in AI-driven decisions.
A data-driven approach: you define success metrics before you build and you measure outcomes after.
Experience working with US-based customers and understanding their businesses, workflows and buyers.
Excellent communication skills and the ability to drive alignment with senior leaders and cross-functional directors.
A builder's mindset: you're comfortable prototyping on your own (with AI tools, no-code, or code) to test ideas quickly.
Big advantage:
Experience in Proptech, vertical SaaS, HRtech or marketplace products.
Experience building platform or data-layer products (integrations, data models, APIs).
Experience leading or mentoring other product managers.
An early-stage or growth-stage startup background.