Forward Deployed Engineer, Arabic Speaking

Role Overview

Senior Forward Deployed Engineer, Arabic Speaking at Salesforce. This is a technical delivery and customer-facing role focused on designing, building, and deploying complex agentic AI solutions directly inside enterprise customer environments.

Company Overview

Salesforce is the #1 AI CRM where humans with agents drive customer success together. The company is leading workforce transformation in the agentic era, with Agentforce representing the future of AI. Salesforce values ambition, innovation, trust, and keeping core values at the heart of all work.

Role Purpose

Own end-to-end technical delivery of agentic AI solutions for Salesforce's most strategic customers, from architecture decisions through production handoff. Lead technical standards, mentor engineers, influence product roadmaps through field insights, and partner with Deployment Strategists to translate complex business challenges into scalable AI solutions.

Key Responsibilities

Technical Ownership & Delivery

• Partner with a Deployment Strategist to own customer outcomes end-to-end as the senior technical authority.
• Own end-to-end build and deployment of agentic AI solutions for strategic customers, from architecture decisions through production handoff.
• Ensure all deliverables meet the highest engineering standards, whether generated by AI tools, colleagues, or written directly by you.
• Develop proofs-of-concept and MVPs quickly, with the judgment to know which decisions can be deferred and which need to be right the first time.
• Provide technical depth on at-risk or strategically critical deployments when senior engineering judgment is needed.

Platform & Systems Architecture

• Design and ship agentic systems on the Agentforce platform: agent logic, tool calls, multi-agent orchestration, deterministic guardrails, and integration patterns that hold up in enterprise environments.
• Own the data lifecycle: model design, processing pipelines, and data readiness for AI applications across Salesforce Data 360, Snowflake, Databricks, and customer-specific platforms.
• Develop reference implementations that become the basis for how other builders approach similar problems.

Problem-Solving & Technical Leadership

• Resolve technical blockers that other engineers cannot, including data integration failures, model deployment issues, orchestration breakdowns, and performance regressions.
• Mentor other engineers through code reviews, pair sessions, and shared work within the same codebases.
• Create reusable assets, patterns, and internal frameworks that become organizational playbooks.
• Build and maintain agent performance dashboards and customer KPI reporting to track deployment health and business outcomes across engagements.

Innovation & Knowledge Development

• Stay at the forefront of AI and data evolution by piloting emerging AI tools, experimenting with new models and frameworks, and sharing learnings with the team and customers.
• Embed AI-supported engineering into daily workflow using tools like Cursor, Claude, and Salesforce coding products such as Vibes.
• Codify what you learn from real customer work into patterns, reusable assets, and internal frameworks.
• Develop and propagate conventions and patterns through the team as a reference for other builders.

Stakeholder & Product Alignment

• Partner with the Deployment Strategist on your team to translate complex customer business challenges into agentic solutions that actually ship.
• Surface field insights directly to Product and Engineering; gaps and edge cases encountered in real customer environments become inputs to the Agentforce roadmap.
• Communicate clearly and credibly with engineering peers, customer architects, and executive stakeholders.
• Influence enterprise software product roadmaps through field engineering insight.

Travel & Customer Engagement

• Travel to customer sites as needed to ensure client success.

Qualifications & Experience

• 6+ years of software engineering or technical delivery experience, with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS environments.
• Bachelor's degree in Computer Science or a related field.
• Deep experience in data modeling, processing, and analytics, with demonstrable proficiency across platforms like Salesforce Data 360, Snowflake, or Databricks.
• Proven integration of LLMs into production systems, with hands-on experience using frameworks like LangChain or LlamaIndex.
• Applied prompt engineering and responsible AI practices in real customer contexts.
• Deep Salesforce platform expertise: Agentforce, Apex, LWC, Flows, and Salesforce APIs.
• Track record of mentoring technical talent and creating reusable assets, frameworks, playbooks, and internal tooling.
• Demonstrated ability to influence enterprise software product roadmaps through field engineering insight.

Skills & Competencies

• Expert proficiency in at least one of Python, JavaScript/TypeScript, Java, or Apex, and conversant in the others.
• Business-level proficiency in both Arabic and English.
• Entrepreneurial, get-things-done mindset focused on fast, impactful delivery, with judgment to know when "fast" is the wrong call.
• Clear and credible communication with engineering peers, customer architects, and executive stakeholders.
• Active engagement with the evolving AI and data landscape: piloting new tools, experimenting with new models, and staying genuinely curious about what's coming next.

Additional Information

Nice-to-Haves

• Salesforce certifications: Administrator, Platform Developer I/II, Agentforce Specialist, or System Architect.
• Familiarity with DevOps/CI-CD practices, observability tooling, or data governance frameworks.
• Experience architecting multi-cloud, multi-system enterprise AI solutions for Global 500 customers.
• Open-source contributions, published technical writing, or conference presentations.

Employment Terms

• Role is based in the Sales job category.
• Travel to customer sites as needed.