Lead AI Forward Deployed Engineer
Overview
In this role, you lead end-to-end delivery of agentic AI solutions for Salesforce’s strategic customers, shaping architecture and production handoff. You work with a Deployment Strategist to ensure high engineering standards and real customer impact. You will pilot new AI tools, mentor others, and translate field insights into product improvements. This is a chance to influence enterprise AI deployments at scale and contribute to Agentforce’s evolution.
Retribuzione / Benefits
- incentive component tailored by grade level
- benefits and resources supporting work-life balance
- career growth opportunities
- access to AI tools to accelerate impact
Responsabilità
- Own end-to-end build and deployment of agentic AI solutions for strategic customers, from architecture decisions to production handoff
- Design and ship agentic systems on the Agentforce platform (agent logic, tool calls, multi-agent orchestration, guardrails)
- Manage data lifecycle and model readiness across Salesforce Data 360, Snowflake, Databricks, and customer platforms
- Resolve blockers in data integration, model deployment, and orchestration to maintain deployment health
- Build and maintain agent performance dashboards and KPI reporting for customer success
- Develop proofs-of-concept and MVPs while making clear deferral vs. correctness decisions
- Codify learnings into reusable patterns, assets, and playbooks for the org
- Mentor engineers through code reviews and paired sessions and share technical depth on critical deployments
- Surface field insights to Product and Engineering to influence the Agentforce roadmap
- Collaborate with Deployment Strategist to translate customer challenges into shippable AI solutions
Requisiti fondamentali
- 6+ years of software engineering or technical delivery with end-to-end ownership of scalable production systems
- Degree in Computer Science or related field
- Proficiency in at least one: Python, JavaScript/TypeScript, Java, or Apex; conversant in others
- Experience integrating LLMs into production and using frameworks like LangChain or LlamaIndex
- Deep experience in data modeling, processing, and analytics across platforms such as Salesforce Data 360, Snowflake, Databricks
- Strong Salesforce platform knowledge: Agentforce, Apex, LWC, Flows, and APIs
- Entrepreneurial, delivery-focused mindset with judgment on when to move fast
- Mentored technical talent and created reusable assets
- Excellent communication with engineers, architects, and executives
- Willingness to travel to customer sites; business proficiency in Italian and English
- CS degree or related field
- Clear and credible communication
- Mentorship and teamwork
- Curiosity and willingness to experiment with new tools
- Python
- JavaScript/TypeScript
- Java
In this role, you lead end-to-end delivery of agentic AI solutions for Salesforce’s strategic customers, shaping architecture and production handoff. You work with a Deployment Strategist to ensure high engineering standards and real customer impact. You will pilot new AI tools, mentor others, and translate field insights into product improvements. This is a chance to influence enterprise AI deployments at scale and contribute to Agentforce’s evolution.
Retribuzione / Benefits
- incentive component tailored by grade level
- benefits and resources supporting work-life balance
- career growth opportunities
- access to AI tools to accelerate impact
Responsabilità
- Own end-to-end build and deployment of agentic AI solutions for strategic customers, from architecture decisions to production handoff
- Design and ship agentic systems on the Agentforce platform (agent logic, tool calls, multi-agent orchestration, guardrails)
- Manage data lifecycle and model readiness across Salesforce Data 360, Snowflake, Databricks, and customer platforms
- Resolve blockers in data integration, model deployment, and orchestration to maintain deployment health
- Build and maintain agent performance dashboards and KPI reporting for customer success
- Develop proofs-of-concept and MVPs while making clear deferral vs. correctness decisions
- Codify learnings into reusable patterns, assets, and playbooks for the org
- Mentor engineers through code reviews and paired sessions and share technical depth on critical deployments
- Surface field insights to Product and Engineering to influence the Agentforce roadmap
- Collaborate with Deployment Strategist to translate customer challenges into shippable AI solutions
Requisiti fondamentali
- 6+ years of software engineering or technical delivery with end-to-end ownership of scalable production systems
- Degree in Computer Science or related field
- Proficiency in at least one: Python, JavaScript/TypeScript, Java, or Apex; conversant in others
- Experience integrating LLMs into production and using frameworks like LangChain or LlamaIndex
- Deep experience in data modeling, processing, and analytics across platforms such as Salesforce Data 360, Snowflake, Databricks
- Strong Salesforce platform knowledge: Agentforce, Apex, LWC, Flows, and APIs
- Entrepreneurial, delivery-focused mindset with judgment on when to move fast
- Mentored technical talent and created reusable assets
- Excellent communication with engineers, architects, and executives
- Willingness to travel to customer sites; business proficiency in Italian and English
- CS degree or related field
- Clear and credible communication
- Mentorship and teamwork
- Curiosity and willingness to experiment with new tools
- Python
- JavaScript/TypeScript
- Java