לוח משרות דרושים מנהל/ת פרויקטים בתחום הבינה המלאכותית, לחיפוש זה נמצאו 51 משרות

Requirements:
All you need is...
Significant senior leadership experience in software engineering and technology.
Deep hands-on understanding of Generative AI, agentic systems, AI-native engineering and modern software architecture.
A proven record of building and delivering innovative software products, platforms or engineering capabilities.
Strong experience across cloud, AI/ML, data and modern engineering technologies.
The ability to combine bold technology vision with disciplined execution.
Experience attracting and leading exceptional technical talent.
Strong executive presence and the ability to influence across a complex global organization.
Experience with BSS, telecommunications or mission-critical B2B software is an advantage, but not essential.

Requirements:
Requirements • 5+ years of hands-on Python development experience, with expertise in building and deploying AI and Machine Learning applications – mandatory. • Extensive hands-on experience with AWS services relevant to AI/ML, including S3, Glue, Athena, SageMaker, Lambda, and Bedrock – mandatory. • Proven experience with Generative AI frameworks such as LangChain, LlamaIndex, or Haystack – mandatory. • Hands-on experience designing and deploying RAG-based applications, along with practical knowledge of Vector Databases such as Pinecone, Weaviate, or ChromaDB and document indexing techniques – mandatory. • Strong understanding of software development principles, including Git version control, clean code practices, and Unit Testing – mandatory. • Strong analytical and problem-solving skills, with the ability to break down complex business challenges into actionable technical solutions – mandatory. • Excellent communication and collaboration skills, with the ability to clearly explain technical concepts to both technical and non-technical stakeholders – mandatory. Nice to Have: Domain Knowledge: Previous experience in the financial services, fintech, or a related highly-regulated industry. Database Experience: Experience with specialized databases such as graph databases (e.g., Neo4j, Amazon Neptune). MLOps Tools: Familiarity with MLOps platforms beyond AWS, such as Kubeflow or MLflow. Education: A Master's or Ph.D. in Computer Science, AI, or a related field.

Requirements:
as an r&d team lead you will
lead and inspire a high-performing team, working on large-scale, complex traffic management and edge computing systems.
drive technical strategy and delivery for our critical traffic control and proxy services, managing complex development projects from initial architecture and design through to production release.
act as a hands-on technical authority, providing code-level guidance, mentorship, and support to your developers.
proactively identify and mitigate risks, bottlenecks, and complex architectural challenges, driving cross-functional stakeholders to deliver on time without compromising quality.
make key technical and strategic decisions to align engineering efforts with high-visibility business goals and the massive demands of ai-driven data growth.
to be an r&d team lead at the company you need
experience: at least 3-4 years of technical leadership experience, paired with hands-on software engineering experience.
leadership skills: proven ability to lead, coach, mentor, and influence highly skilled developers in a fast-paced environment.
technical expertise: deep expertise in high-scale back-end development with JAVA /go/ C #. experience with reverse proxies, caching mechanisms, or network traffic management is a strong advantage.
ai-assisted development: experience incorporating agentic ai tools across the entire software development lifecycle.
systems architecture: a strong background in the architecture and implementation of scalable, concurrent, low-latency, fault-tolerant distributed systems.
delivery & risk management: a strong track record of managing complex software projects, hitting key milestones, and pre-emptively resolving technical challenges.
adaptability: a thriving mindset in a fast-paced, context-switching, and highly driven environment.

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:
7+ years of software engineering experience, with at least 3 years focused on AI/ML in production environments
Hands-on experience with both Dev (backend services, APIs, microservices) and DevOps (CI/CD, infrastructure, observability, cloud operations)
Proven experience building or integrating AI/ML solutions in cloud-native, distributed systems (AWS preferred)
Strong understanding of observability concepts: metrics, logs, traces, alerting, anomaly detection T
Experience driving technical initiatives across multiple teams without direct authority
Excellent communication skills - ability to translate complex AI concepts for non-AI engineers and push for outcomes in a multi-stakeholder environment
These would also be nice:
Experience with LLMs, RAG pipelines, or AI agents applied to engineering operations (AIOps)
Familiarity with Kubernetes, Grafana, or similar operational tooling
Background in media tech, video streaming, or telecom platforms
Experience with Databricks, MLflow, or similar ML platform tooling
Track record of introducing AI tooling that improved team velocity or system reliability at scale.

Requirements:
High Ownership & Seniority: You take full end-to-end responsibility for complex growth projects, domains, and metrics with minimal guidance.
Mastery of AI Builder Tools: Advanced hands-on experience building, prototyping, and shipping with modern AI tools (Claude Code, Cursor, Replit, v0, Bolt.new, custom scripts, or LLM agents).
Proven Full-Stack Growth Mindset: Deep understanding of consumer products, acquisition mechanics, CRO, messaging, onboarding journeys, and retention dynamics.
Proven Builder Track Record: Demonstrated experience developing AI-driven projects, automations, scrapers, sub-products, apps, content systems, or custom workflows independently.
Leadership & Scaling Potential: Strong communication skills and the capability to lead cross-functional initiatives, guide junior team members, or step into a Team Lead role.
Data Literacy & Analytical Rigor: Ability to query data, analyze performance across the conversion funnel, and make fast, data-informed decisions.
Initiative & High Velocity: You take action without waiting for direction, learn new technologies on the fly, and thrive in ambiguous, fast-moving environments.
Advantage: Prior experience in high-scale performance marketing, UA operations, or consumer software growth.

Requirements:
High ownership: You take responsibility for projects end-to-end with minimal guidance.
Hands-on with AI tools: Experience building with tools like Claude Code, Cursor, Replit, or similar.
Growth mindset: You're drawn to consumer products and have a strong sense for what drives clicks, sign-ups, and retention.
Proven builder: You've developed AI-driven projects such as agents, automations, apps, content systems, or custom workflows.
Initiative: You take action without waiting for direction and approach problems in creative ways.
Background or experience in marketing and growth is a plus.

Requirements:
Strong hands-on experience building and deploying AI-powered solutions Proven experience with AI, automation, digital transformation, or process improvement within organizations. Strong technical capabilities paired with a strong business understanding. Ability to translate business challenges into practical, working solutions. Experience leading cross-functional initiatives in a matrix organization. Ability to move comfortably between hands-on execution, business process analysis, and strategic planning. Strong analytical, execution, and stakeholder management skills, including building business cases and aligning priorities and investments with senior leadership. A builder mindset and willingness to roll up your sleeves and deliver. The leadership potential to build capabilities, recruit and develop a team, and take on broader responsibility as Landa's AI transformation scales.

Requirements:
6+ years of experience as a backend developer.
2+ years developing AI/ML solutions.
1+ years in a technical leadership role.
Strong understanding of LLMs, prompt engineering, and model orchestration.
Strong understanding of ETL pipelines, data preprocessing, and training workflows.
Proficiency in Python, TypeScript (Bonus), Node.js (Bonus).
Proficient in Statistics, Fraud detection and Computer vision (Bonus) models.
Experience integrating ML models into production systems with CI/CD pipelines.
Solid grasp of FinTech data flows, security protocols, and compliance requirements.
Excellent communication and mentoring skills.
B.Sc. in Computer Science or related field (M.Sc. a plus).

Requirements:
You are a true Quality Executioner at heart, thriving on meticulous execution and a commitment to seeing projects through to completion with exceptional detail and efficiency.
Bring a proven ability to develop and manage comprehensive chatbot strategies and roadmaps, aligning them with broader business objectives.
Possess strong stakeholder management and communication skills, adept at building consensus and articulating complex information clearly across different audiences.
Demonstrate experience in mentoring and leading team members, fostering their development and providing hands-on support.
Exhibit a deep understanding of data analysis and KPI monitoring, using insights to drive measurable improvements and strategic pivots.
Hands on experience with AI Chatbot prompting providing customer facing solutions
Fluent English is a must
Nice to have
Familiarity with the Forethought platform.

Requirements:
Experience: 7+ years in Data Engineering, BI, Data Science, or Technical Leadership, Managerial Experience: with 3+ years managing technical teams. Technical Depth: Proven hands-on experience with modern cloud data platforms (Snowflake, BigQuery, Databricks, or AWS Services) and ETL/ELT pipelines. Applied AI / GenAI: Practical experience deploying production ML models, LLMs, RAG systems, or AI agents. Systems Integration: Track record of integrating enterprise ecosystems (ERP, CRM) with large-scale telemetry and logs. Governance & Security: Familiarity with security, privacy, and compliance standards (SOC 2, GDPR). Communication & Leadership: Strong ability to influence cross-functional stakeholders and translate complex technical topics into business strategy. Education: B.Sc./M.Sc. in Computer Science, Information Systems, Engineering, or a related field.

Requirements:
Experience at building and shipping AI agents and processes in the last 18 months in a GTM or business operations context, not purely research.

Experience leading at least 2-4 people.

Highly technical, likely ex-engineer, able to build hands-on and not just direct.

Comfortable operating at CEO speed.

RevOps experience is a strong advantage - understands GTM workflows end-to-end, including pipeline, CRM hygiene, Gong, Salesforce, lead routing, and post-sales handoffs.

Experience working embedded with a sales or marketing team, building AI on top of their actual workflows, is a strong advantage.

Requirements:
Bachelors degree in Information Systems, Industrial Engineering, Business Administration, Computer Science, or a related field
Minimum 6 years of experience in one or more of the following areas: business transformation, AI transformation, strategy execution, PMO, business operations, or cross-functional program management.
Proven experience supporting or driving AI-related initiatives, including AI adoption, implementation, or integration into business processes.
Strong ability to manage multiple stakeholders, workstreams, dependencies, and priorities in parallel.
Experience working with senior stakeholders and influencing without direct authority.
Excellent communication, presentation, analytical, and execution capabilities.
Fluent English, written and verbal, with the ability to communicate effectively with senior leadership and global stakeholders.
Ability to connect strategy, business needs, product thinking, AI capabilities, and operational execution.
Experience in global consulting firms, such as Big 4, Deloitte Monitor, McKinsey, BCG, Bain, Accenture, or similar, is a significant advantage.