FDE SWAT

Overview

As a Forward Deployed Engineer in the FDE SWAT team, you diagnose and resolve critical live deployments, driving stable performance across Agentforce and Salesforce platforms. You own end-to-end issues, collaborate with Product and Engineering, and share learnings to improve future deployments. You work directly with customers and cross-functional teams to translate challenges into practical AI-driven solutions. This role offers hands-on work at scale with enterprise clients and a direct impact on platform quality and customer outcomes. You will join a mission to advance agentic AI within Salesforce's AI-powered CRM ecosystem.

Retribuzione / Benefits

• incentive component tailored by grade level

Responsabilità

• Develop AI agents and experiences that perform real actions for organizations
• Design agent intelligence including prompts, reasoning, and tool integration
• Own components end-to-end from architecture to production deployment and observability
• Build and integrate data pipelines with Salesforce Data 360, Snowflake, Databricks, and customer data platforms
• Create and maintain dashboards and KPI reporting to monitor deployment health
• Contribute to proofs-of-concept and MVPs and move from sketch to deployable quickly
• Co-build with customers and partners, sharing best practices and enablement
• Identify recurring issues and provide actionable insights to improve quality and resilience
• Collaborate with Deployment Strategist to translate customer challenges into deployable solutions

Requisiti fondamentali

• 3+ years of software engineering or technical delivery experience with at least one production system
• Degree in Computer Science or related field
• Prior customer-facing technical delivery experience
• Fluency in Python, JavaScript/TypeScript, Java, or Apex
• Hands-on experience with LLMs and prompt engineering
• Strong data modelling, API design, and integration pattern skills
• Ability to communicate with sales teams and customer architects
• Proven track record of shipping quality code and evaluating AI outputs
• Willingness to travel ~25%
• collaborative mindset
• strong communication under pressure
• curiosity and fast-learning in AI landscapes
• AI/LLM stack development
• full-stack development
• prompt engineering