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Red HatDesign and deliver Red Hat OpenShift, Kubernetes, and hybrid cloud solutions for enterprise customers. Lead customer engagements focused on infrastructure, automation, and application delivery.
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Quantum Machines व्यावहारिक क्वांटम कंप्यूटिंग के लिए प्रौद्योगिकियाँ विकसित करती है और उन नियंत्रण प्रणालियों पर ध्यान केंद्रित करती है जो शोधकर्ताओं तथा इंजीनियरों को उन्नत क्वांटम हार्डवेयर संचालित करने में सहायता देती हैं। इसका Quantum Orchestration Platform क्वांटम प्रयोगों को प्रोग्राम करने, प्रबंधित करने और अनुकूलित करने के लिए आवश्यक उपकरणों को एक साथ लाता है तथा सिस्टम विकास से लेकर कार्यान्वयन तक के काम में सहायता करता है। कंपनी के क्वांटम वैज्ञानिकों और इंजीनियरों की टीम ऐसे बुनियादी ढाँचे पर काम करती है जिसका उद्देश्य क्वांटम प्रौद्योगिकियों को शोध परिवेशों से वास्तविक दुनिया के अनुप्रयोगों तक पहुँचाना है।
CTO AI Solutions Builder (Remote, Israel)
Build AI agents, automations, internal applications, and knowledge-management systems for Quantum Machines. Drive adoption across the CTO organization and develop customer-facing technical content.
विवरण
- Build and deploy AI applications, agents, custom skills, automated workflows, and internal tools
- Architect, develop, deploy, and maintain AI solutions in IT- and DevOps-managed environments
- Choose appropriate tools and establish a governed, discoverable knowledge-management system for internal and customer-facing content
- Create technical onboarding curricula tailored to the CTO organization
- Identify and prioritize valuable AI opportunities across Customer Success, Support, Product, and the broader CTO organization
- Integrate business systems, data warehouses, APIs, and vector stores to enable dependable retrieval and automation
- Apply version control, output validation, error handling, and monitoring to prompts, skills, and multi-agent workflows
- Track adoption and outcomes, lead enablement, document practical guidance, and expand usage
- Define technical and hosting needs in partnership with IT and DevOps
- Deploy solutions in line with corporate security and data-governance requirements while helping establish practical AI standards
- Partner with the Marketing AI builder to share reusable components and prevent duplicated effort
आवश्यकताएँ
- Take ownership of greenfield challenges, identify friction, challenge low-value requests, and deliver practical solutions
- Understand system architecture, data flows, and security while evaluating operational impact
- Work hands-on with emerging AI models, SDKs, vector databases, and agent frameworks
- Translate non-technical workflows into useful solutions and communicate requirements to IT and Security
- Organize complex expert knowledge into structured, usable systems
- Bring at least three years of hands-on software, application, or data engineering experience shipping production tools
- Demonstrate strong Python and/or TypeScript/JavaScript skills, including code reading, debugging, and auditing
- Have practical LLM development experience covering prompt and context design, agents or agentic workflows, and API-based model integration
- Understand SQL, data modeling, REST APIs, and webhooks
- Have experience with a data warehouse such as Snowflake
- Communicate infrastructure and security requirements to IT and DevOps and build safely within established guidelines
- Be fluent in written and spoken English
- Experience with RAG, retrieval systems, vector databases such as Pinecone, Qdrant, or Chroma, or agent frameworks such as LangChain, LlamaIndex, or CrewAI is advantageous
- Experience with knowledge-base and documentation platforms such as Confluence, Guru, or Document360 is advantageous
- Experience with Salesforce, Jira, Slack, Microsoft 365, or automation platforms such as Workato, n8n, or Make is advantageous
- A degree or academic background in Computer Science or Software Engineering is advantageous
- Experience in a B2B deep-tech, hardware, or scientific-instrumentation company is advantageous
लाभ
- The listing does not specify benefits, perks, or additional compensation.
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