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Technical Architect

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Salesforce

10,000+ employees

Founded 1999

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Salesforce is a leading cloud-based software company that provides a comprehensive customer relationship management (CRM) platform. The platform connects all company data and teams on an integrated, AI-driven system to improve sales, customer service, and marketing efforts. Salesforce offers scalable solutions for businesses of all sizes, including small and medium enterprises, and provides industry-specific solutions to modernize operations, save time, and reduce costs. Salesforce also offers educational resources through Trailhead and a wide selection of apps on AppExchange to extend its CRM capabilities.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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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