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Salesforce

Builds cloud software for customer relationships

Forward Deployed Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeMadrid, SpainNo salary listed

About the Job

Requirements

  • You have 5+ years of experience in software engineering, data engineering, or technical implementation, including a production data solution you can explain in detail.
  • You have a bachelor's degree in Computer Science or equivalent practical experience.
  • You have hands-on experience implementing Salesforce Data 360 (Data Cloud) or a comparable enterprise data platform across ingestion, modeling, identity, insight, activation, and operations.
  • You have hands-on experience building data pipelines and integrations using at least one enterprise data platform or technology, such as Snowflake, Databricks, BigQuery, Redshift, Kafka, cloud object storage, or an enterprise MDM platform.
  • You are proficient in SQL and can build, debug, and optimize multi-table queries, joins, filters, transformations, and validation checks.
  • You are fluent in at least one implementation language used in enterprise delivery—Apex, Java, Python, or JavaScript/TypeScript—and are willing to learn the others as needed.
  • You understand data modeling, APIs, integration patterns, batch and streaming processing, and the practical differences between copied, federated, and Zero Copy data access.
  • You have built retrieval systems for AI applications, such as vector databases, search indexes, embedding pipelines, or knowledge bases, and can explain design decisions behind chunking, indexing, and relevance.
  • You have implemented secure service-to-service integration patterns (OAuth, SAML, event-driven architectures) and are conversant in emerging agent protocols such as MCP and agent-to-agent communication.
  • You can implement secure data access and rigorously test permissions, entitlements, consent, user context, restricted populations, and negative test cases.
  • You diagnose technical problems methodically, use logs and query evidence, isolate product behavior from configuration errors, and document reproducible results.
  • You can implement against a documented architecture, explain what you built to customer technical teams, and recognize when a question requires an architect or security owner.
  • You have delivered alongside customers, partners, professional services, or internal implementation teams in deadline-driven environments.
  • You are excited to work directly with customer administrators, developers, data engineers, and architects.
  • You have relevant certifications in Salesforce Agentforce, Data 360, and the Salesforce Platform.

Responsibilities

  • Configure and develop directly in customer sandboxes and production using Data 360 configuration, SQL, Apex, Flow, Python, the REST Query API, the Interaction SDK, Salesforce DX, CLI, Git, Data Kits, and deployment tooling as required, following security, change-management, and release controls.
  • Build ingestion, harmonization, and identity resolution across batch and streaming sources. Materialize views of data optimized for specific application, analytical, and agentic workloads, tuning latency and cost tradeoffs to meet use-case requirements. Work with customer data and AI teams to align implementations with existing strategies such as data mesh and data fabric.
  • Create representative test data and validate expected outcomes across happy paths, edge cases, access boundaries, hierarchy behavior, failure conditions, and customer-scale volumes.
  • Design, build, and maintain the AI data integration layer—including retrieval-augmented generation, vector databases, search indexes, and knowledge bases—that grounds Agentforce solutions in accurate, real-time enterprise data.
  • Design and implement protocols, including Model Context Protocol and agent-to-agent communication, that govern, monitor, and ensure efficient collaboration among specialized AI agents.
  • Implement robust, scalable, and secure data integration patterns that connect Agentforce to enterprise applications and enable communication between AI agents.
  • Apply data management expertise to ensure secure integration, transformation, and governance of structured and unstructured data across the Salesforce ecosystem, including CRM and Data Cloud, and external systems.
  • Apply knowledge of message queues, event-driven architecture, and distributed systems to build resilient workflows and implement secure authentication and authorization protocols such as OAuth and SAML, ensuring agent actions comply with enterprise security policies.
  • Troubleshoot ingestion failures, mapping defects, schema drift, identity anomalies, query behavior, activation latency, API errors, permissions, and consumption issues methodically, using logs and query evidence to isolate product behavior from configuration error.
  • Compare viable techniques within the approved architecture, document measured tradeoffs, and recommend the most maintainable implementation to the responsible architect or technical lead.
  • Use AI tooling, including Data 360 APIs and MCP Servers, to automate the build process and reduce customers’ time to value.
  • Work alongside customer technical teams and partners through pairing, code reviews, and configuration reviews. Package reusable metadata, scripts, queries, tests, and runbooks so the solution can be reproduced and supported. Support deployment, validation, production handoff, and early stabilization, leaving clear ownership and known limitations.
  • Surface reproducible platform gaps and edge cases, with live evidence, impact, and expected behavior, directly to Product and Support.

About the Company

Salesforce

Builds cloud software for customer relationships

Salesforce sells cloud software that helps businesses manage sales leads, customer service, marketing, and online commerce from shared customer records. Its flagship Sales Cloud tracks accounts and deals, while Service Cloud organizes support cases and Agentforce builds AI assistants that act on company data. Teams access these tools through a browser and connect outside apps and data sources, with Slack for work messages and Tableau for visual analysis. Salesforce earns most of its revenue from software subscriptions and support, with professional services for implementation and training. Marc Benioff co-founded Salesforce in 1999, and its headquarters are in San Francisco, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Francisco, CA
Founded
1999

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