Inactive
S

Salesforce

Builds cloud software for customer relationships

Forward Deployed Engineer

AI Application EngineeringPosted on Jul 7
Full-timeEspoo, FinlandNo salary listed

About the Job

Requirements

  • Have at least 3 years of software engineering or technical delivery experience and a production system to discuss, ideally in an artificial intelligence technology stack, full-stack development, or working with frontier models.
  • Have a degree in Computer Science or a related field.
  • Have prior customer-facing technical delivery experience in consulting, professional services, or forward deployed engineering.
  • Be fluent in at least one of Python, JavaScript/TypeScript, Java, or Apex, and be willing to learn additional languages as needed.
  • Have hands-on experience with large language models and prompt engineering, including the ability to explain prompt failures and proposed changes.
  • Understand data modeling, application programming interfaces, and integration patterns well enough to design them.
  • Be able to engage effectively with sales teams and customer architects.
  • Ship quality code and evaluate artificial intelligence outputs with engineering rigor.
  • Stay current with the evolving artificial intelligence and data landscape by piloting tools, experimenting with models, and learning about emerging developments.
  • Be willing to travel approximately 25% of the time and work directly alongside customers.

Responsibilities

  • Develop artificial intelligence agents and experiences that take actions for organizations and are deployed in production.
  • Design agent intelligence, including prompts, reasoning, tool calls, and integration with customer systems, using the agentic artificial intelligence platform and current large language model techniques.
  • Own technical components end-to-end, from architecture selection through deployment, validation, and production observability.
  • Build and integrate data pipelines using Salesforce Data 360, Snowflake, Databricks, and customer data platforms; model the data, deliver the pipeline, and validate its output.
  • Build and maintain agent performance dashboards and customer key performance indicator reporting to track deployment health and business outcomes.
  • Contribute to proofs of concept and minimum viable products, moving them from initial concepts to deployable solutions quickly.
  • Co-build solutions alongside customers and partners, sharing best practices and enablement during delivery.
  • Share platform gaps, edge cases, and field insights with senior engineers and the product team.
  • Partner with the Deployment Strategist to translate customer business challenges into agentic solutions that are delivered.

Desired Qualifications

  • Salesforce platform experience or certifications, such as Administrator, Platform Developer I, or Agentforce Specialist.
  • Familiarity with agent frameworks such as LangChain and LlamaIndex, and orchestration patterns.
  • Hands-on experience with cloud data platforms such as Snowflake, Databricks, or BigQuery.
  • Experience in specialist artificial intelligence delivery areas such as data engineering, platform architecture, or headless deployments.

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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