Technical Architect

🕒 vor 22 Tagen

🌽 Illinois, Kansas, +1 weitere Bundesländer – Remote

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💵 $190.750 - $255.150 / Jahr

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

🔙 Backend-Entwickler

🦅 H1B-Visum-Sponsor

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👻 Geisterscore 0%

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🗣️🇺🇸🇬🇧 Englisch erforderlich

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Salesforce

10.000+ Mitarbeiter

GegrĂźndet 1999

💼 Beratung

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Salesforce ist die weltweit vertrauenswürdigste Plattform für Customer Relationship Management (CRM), die entwickelt wurde, um Marketing-, Vertriebs-, Handels-, Service- und IT-Teams zu vereinen und Kundenbeziehungen zu verbessern. Es bietet Lösungen wie Sales Cloud zum Abschluss von Geschäften, Service Cloud für Kundensupport und Marketing Cloud zum Aufbau dauerhafter Kundenbeziehungen. Salesforce fördert das Wachstum von Unternehmen jeder Größe mit seiner umfassenden Plattform, die autonome KI-Agenten und vereinheitlichte Daten umfasst. Das Unternehmen unterstützt Lernen durch sein Trailhead-Programm und bietet geführte Pfade zur Entwicklung von Salesforce-, digitalen und Soft Skills an. Über 150. 000 Unternehmen vertrauen Salesforce, das nicht nur durch seine Technologie, sondern auch durch sein Engagement für bessere Geschäftspraktiken und Gemeinschaften hervorsticht.

Beschreibung

• Serve as a pre-sales, customer-facing enterprise domain expert for Data & AI Cloud solutions • Help customers address complex data and AI challenges involving unified data platforms, lakehouses, agentic AI systems, and LLM-powered applications • Use structured discovery to uncover business and technical requirements and translate them into solution architectures • Lead technical and business discussions across enterprise data and AI programs from strategy through architecture and deployment • Select technologies and patterns aligned with customer goals using cloud-native best practices • Help sales teams develop repeatable propositions and go-to-market strategies • Deliver solution best practices, reference architectures, enablement sessions, and industry summits • Design, develop, deploy, and manage agentic AI systems and enterprise generative AI solutions • Architect data pipelines, semantic layers, feature stores, orchestration layers, and persistent context architectures • Travel domestically for customer engagements and team events

🎯 Anforderungen

• Hands-on experience with cloud data warehouse and lakehouse platforms such as Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse • Strong SQL skills and data modeling across structured, semi-structured, and unstructured data • Familiarity with dbt or Spark is a plus • Familiarity with machine learning fundamentals, including feature engineering, model training pipelines, inference patterns, and vector/embedding-based retrieval • Practical experience with agentic AI or generative AI, including an LLM or agent production deployment, proof of concept, or side project • Experience using AI coding tools such as Copilot, Cursor, or Claude Code; Python proficiency strongly preferred • Deep knowledge of enterprise data platforms and AWS, GCP, or Azure cloud architectures • Knowledge of data modeling, MDM, identity resolution, data quality, governance, and lineage • Knowledge of APIs, event streaming, Kafka/Pub-Sub, and ETL/ELT patterns • Knowledge of process orchestration and automation • Knowledge of network, application, and information security principles • Willingness to work with Python, SQL, JavaScript, Java, or similar code • Ability to translate complex business and technical requirements into solution narratives for executive, technical, and business audiences • Strong written, verbal, and presentation skills • Excellent time management across concurrent engagements • Willingness and ability to travel domestically • Bachelor's degree in Computer Science, MIS, Data Science, Software Engineering, or another STEM field, or equivalent experience • B.S. in Computer Science, Software Engineering, or MIS • Knowledge of related applications, relational databases, and ERP technologies • Minimum of 4 years of professional experience • Hands-on experience developing, deploying, and managing agentic AI systems • Understanding of autonomous agents, tool use, heterogeneous data systems, cloud warehouses, APIs, and vector stores • Experience with agentic frameworks such as LangChain, LangGraph, CrewAI, or AutoGen • Working understanding of LLMs, prompt engineering, tool calling, and RAG patterns • Experience designing persistent agent context and memory layers • Experience architecting generative AI solutions with API gateways, model management platforms, embedding pipelines, vector databases, and production data flows • Deep understanding of lakehouse and unified data architecture patterns • Experience designing orchestration layers for complex, multi-step business processes

🏖️ Vorteile

• Time off programs • Medical insurance • Dental insurance • Vision insurance • Mental health support • Paid parental leave • Life insurance • Disability insurance • 401(k) • Employee stock purchasing program • Incentive compensation may apply • Equity may apply

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