דרושים » AI » Field AI Engineer

Requirements:
Engineering Skills:
4-6+ years of software engineering experience with a track record of shipping production systems
Hands-on experience with AI orchestration frameworks: LangChain, LangGraph, LangFlow, or similar (LlamaIndex, CrewAI, AutoGen)
Strong Python skills and hands-on experience building AI-powered applications in production
Deep knowledge of LLMs, RAG architectures, agent patterns, tool use, and prompt engineering
Experience with vector databases and semantic search (Pinecone, Weaviate, pgvector, or similar)
Solid fundamentals: API design, microservices, data pipelines; cloud experience (AWS) is an advantage
The Differentiators:
People person - you genuinely enjoy working with non-technical colleagues and build trust naturally with stakeholders at every level
Can-do mindset - you find a way and ship, rather than waiting for perfect conditions
Team player - you operate with autonomy but share context, invite feedback, and make those around you better
Self-taught by nature - you learn new frameworks in days and apply them in production; you dont wait for someone to tell you whats next
Outcome-obsessed - you measure success by business impact, not technical elegance
Nice to Have:
Experience with automation platforms (n8n, Workato, or similar)
Familiarity with enterprise tooling ecosystems (Salesforce, NetSuite, BI, HRIS)
Background in solutions engineering, technical consulting, or product management.

Requirements:
3+ years of experience managing B2B SaaS products, ideally within AI-driven solutions or services.
Strong technical foundation, with understanding in Kubernetes, cloud-native technologies, or similar platforms being highly advantageous.
A data-driven mindset with the ability to approach challenges strategically and identify impactful solutions.
You know to operate independently, move quickly, and keep work organized.
Excellent verbal and written communication abilities, capable of translating complex technical concepts for various audiences, including non-technical stakeholders.
Proven ability to work effectively across diverse teams, managing multiple stakeholders and aligning priorities to drive product success.

Requirements:
What should you bring to the table?
3+ years of experience in customer-facing, execution-heavy roles such as Sales Engineering, Solutions Architecture, Professional Services, or Customer Success.
Proven experience working directly with customers to implement and adopt complex products.
Strong technical aptitude and comfort working with AI-powered products.
A highly customer-centric mindset and willingness to roll up your sleeves and stay engaged until things actually work.
Excellent presentation and communication skills, with the ability to explain complex concepts clearly and practically.
Native-level English.
Curiosity, adaptability, and enthusiasm for driving AI adoption at scale.
Ability to work independently, learn quickly, and thrive in a fast-paced, global, agile environment.

Requirements:
Minimum 7 years of full-stack development experience, with at least 2 years in a leadership role.
Strong experience with Node, React, Python, SQL or any equivalent language.
Experience with cloud, DevOps, and modern tooling (e.g., GCP/AWS, Kubernetes, Docker, CI/CD).
Excellent problem-solving skills and ability to handle multiple projects in a fast-paced environment.
Strong communication skills, with the ability to interact effectively with both technical and non-technical stakeholders.
Passion for innovation, AI technology, and building scalable, impactful products.
BSc in Computer Science, or Engineering degree is a plus.
Ability to thrive in a fast-paced, dynamic environment with a proactive and goal-oriented mindset.

Requirements:
Technical Expertise:
Programming: Advanced proficiency in Python for backend development and AI applications
GenAI Mastery: Deep understanding of large language models (LLMs) and experience with major model APIs (OpenAI, Anthropic, Google, etc.)
Multi-Agent Systems: Expertise in designing and implementing GenAI multi-agent architectures
Prompt Engineering: Advanced skills in prompt design, optimization, and engineering techniques
Cloud Platforms:
Required: Hands-on experience with AI services in at least one major cloud platform (GCP, Azure, or AWS)
Advantage: Experience across multiple cloud platforms (AI Search, Vertex AI, SageMaker, etc.)
Development Frameworks: Experience with GenAI frameworks like LangChain and cloud-based retrieval services
Software Engineering: Strong background in microservices architecture, API development, and production system design
AI/ML Fundamentals: Solid understanding of deep learning principles and GenAI techniques
Containerization (Advantage): Experience with Docker and Kubernetes for deployment and orchestration
OCR Technologies (Advantage): Experience with Optical Character Recognition systems and document processing
Data Pipelines (Advantage): Experience building and maintaining data processing pipelines
Professional Experience
Mid+ Level Experience: 2+ years in AI/ML development with significant GenAI project experience
Production Systems: Proven track record of deploying and maintaining AI solutions in production environments
Client-Facing Experience: Comfortable with technical presentations and requirement gathering sessions
Education & Background
Preferred: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related technical field
Alternative: Demonstrated industrial experience in developing deep learning and GenAI solutions (degree not required with strong portfolio)
Soft Skills
Problem-Solving: Excellent analytical and creative problem-solving abilities
Communication: Strong technical communication skills for both technical and non-technical audiences
Collaboration: Proven ability to work effectively in cross-functional teams
Adaptability: Thrives in fast-paced environments and eager to learn emerging technologies
Consulting Mindset: Ability to understand client needs and provide strategic technical guidance.

Requirements:
3+ years leading full-stack engineering teams, with a strong preference for staying hands-on with code and architecture.
5+ years of strong full-stack software engineering experience.
Deep expertise across AWS, Kubernetes, backend services, APIs, databases, and modern frontend/UI development.
Strong backend skills in Python, Node.js, Go, or similar languages.
Proven track record owning complex product domains from initial design through production and ongoing evolution.
Excellent product intuition and the ability to collaborate effectively with Product, Design, field teams, and customers.
Genuine curiosity about AI coding agents, modern developer workflows, and the future of AI-assisted software engineering.

Requirements:
4-7 years of experience in Business Systems, RevOps systems, Data/Systems Engineering, or similar hands-on technical roles
Proven experience building and deploying end-to-end workflows and automations in business environments
Hands-on experience with LLM tools and prompt/workflow engineering, with a focus on reliability and real-world use cases
Experience with automation/orchestration tools (e.g., workato) and/or agent frameworks
Strong experience integrating and extending CRM systems (e.g., Salesforce), including workflows, data models, and system integrations
Experience working with APIs, system integrations, and data flows across multiple platforms
Experience supporting GTM / RevOps in a SaaS environment
Strong analytical and problem-solving skills, with the ability to prioritize based on business impact
High ownership and ability to operate independently from idea to production
Strong communication skills and ability to work effectively with both technical and non-technical stakeholders

Requirements:
5+ years of solid backend and server-side development experience, building complex and highly scalable systems.
Proven proficiency in at least one general-purpose language (Python preferred, though not required).
A natural collaborator who builds trust across functions - comfortable working with product, business development, account management, and other non-technical partners, and able to translate between their needs and technical solutions.
Strong product-oriented thinking, with the ability to elicit, refine, and prioritize requirements from non-technical stakeholders.
A deep sense of ownership, some DevOps experience, and the drive to develop, deploy, and operate projects from start to finish.
Able to navigate an organization and influence without authority - communicating effectively with engineers and managers as well as VP and C-suite leadership.
A bias toward driving change: you spot opportunities to improve processes and accelerate technology adoption, and you act on them.
High proficiency with AI-assisted coding tools such as Copilot, Cursor, or equivalents.
Hands-on experience with public cloud platforms (AWS, GCP, or Azure).
Fluency in written and spoken English.
Bonus Points If You:
Are experienced with agentic coding tools like Claude Code or Copilot CLI.
Have familiarity with Strands Agents (or comparable agentic frameworks), RAG architectures, and Bedrock.
Have worked with MCP (Model Context Protocol).
Are comfortable operating in containerized environments.

Requirements:
Bachelors degree in Computer Science, Engineering or a related field, with focus on AI.
3+ years of hands-on experience in AI/ML engineering, ideally within the fintech industry or a related sector, with a track record of deploying AI agents or agentic workflows in production
Proficiency in Python and SQL for data manipulation, analysis, and AI system building.
Deep experience with LLMs and prompt engineering, including systematic evaluation of enterprise AI solutions
Experience with building RAG systems and Conversational chatbots - Advantage
Experience with cloud platforms (AWS preferred) for deployment and AI-Ops practices.
Analytical Mindset: You bring strong statistical reasoning and business acumen, with the ability to critically assess AI solutions and their real-world impact.
Project Management: You can manage and prioritize multiple tasks, balancing short-term and long-term goals to deliver timely, high-impact results.

Requirements:
2+ years of proven experience in delivering technological trainings and enablement programs, combined with hands-on involvement in technology implementation projects.
Academic degree in a technological field and/or a degree in Learning Technologies / Instructional Design.
Strong technological background with the ability to work hands-on with enterprise systems as part of implementation projects.
Experience working directly with large and/or international clients, including delivery in diverse organizational environments.
Proven ability to design, deliver, and facilitate professional trainings, workshops, and onboarding sessions, including creation of supporting learning materials.
Excellent presentation and communication skills in English - fluent spoken and written.
Familiarity with Microsoft 365 technologies such as Teams, SharePoint, OneDrive, Power Automate, or Power Apps - a significant advantage.
Exposure to AI-based productivity tools, including Microsoft Copilot or similar solutions - an advantage.
Ability to translate business and user needs into practical, usable technology solutions.
Strong interpersonal skills, independence, and comfort working in client-facing, delivery-oriented roles.