وصف الوظيفة
Role Overview
Forward Deployed Engineer, Arabic Speaking at Salesforce. This is a senior technical role responsible for 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 as the future of AI. Salesforce values innovation, ambition, action, and trust at its core.
Role Purpose
Lead end-to-end technical delivery of agentic AI solutions for Salesforce's most strategic customers. You will serve as the senior technical authority, ensuring deliverables meet the highest engineering standards, mentor other engineers, set engineering standards for how agentic AI gets deployed at scale, and partner closely with a Deployment Strategist to own outcomes from architecture decision through production handoff.
Key Responsibilities
Technical Ownership & Delivery
- Own end-to-end build and deployment of agentic AI solutions for Salesforce's most strategic customers, from architecture decisions through production handoff.
- Design and ship agentic systems on the Agentforce platform, including agent logic, tool calls, multi-agent orchestration, deterministic guardrails, and integration patterns that hold up in enterprise environments.
- 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.
- Resolve technical blockers that other engineers cannot, including data integration failures, model deployment issues, orchestration breakdowns, and performance regressions.
- Provide technical depth on at-risk or strategically critical deployments when senior engineering judgment is needed.
Data & AI Systems
- Own the data lifecycle, including model design, processing pipelines, and data readiness for AI applications across Salesforce Data 360, Snowflake, Databricks, and customer-specific platforms.
- Build and maintain agent performance dashboards and customer KPI reporting to track deployment health and business outcomes across engagements.
Knowledge Transfer & Standards
- Mentor other engineers through code reviews, pair sessions, and shared work.
- Codify what you learn. The patterns, reusable assets, and internal frameworks that come out of your real customer work become the playbooks the rest of the organization draws from.
- Set engineering standards that define how agentic AI gets deployed at scale; other Builders look to your work as reference.
Stakeholder Partnership & Insights
- 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. The gaps and edge cases you encounter in real customer environments become valuable inputs to the Agentforce roadmap.
Continuous Innovation
- Stay at the forefront by piloting emerging AI tools, experimenting with new models and frameworks, and sharing what you learn with your team and customers.
- Use AI-supported engineering tools including Cursor, Claude, and Salesforce coding products like Vibes embedded in your daily workflow.
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.
- Degree in Computer Science or a related field.
- Expert proficiency in at least one of Python, JavaScript/TypeScript, Java, or Apex, and conversant in the others.
- Integrated LLMs into production, used frameworks like LangChain or LlamaIndex, and applied prompt engineering and responsible AI practices in real customer contexts.
- Deep experience in data modeling, processing, and analytics, with demonstrable proficiency across platforms like Salesforce Data 360, Snowflake, or Databricks.
- Deep Salesforce platform expertise, including Agentforce, Apex, LWC, Flows, and Salesforce APIs.
- Track record of mentoring technical talent and creating reusable assets, frameworks, playbooks, and internal tooling.
- Business-level proficiency in Arabic and English.
Skills & Competencies
- Entrepreneurial, get-things-done mindset focused on fast, impactful delivery with the 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
- Ability to travel to customer sites as needed to ensure client success.
- Nice-to-haves: Salesforce certifications (Administrator, Platform Developer I/II, Agentforce Specialist, 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; track record of influencing enterprise software product roadmaps through field engineering insight; open-source contributions, published technical writing, or conference presentations.
- Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. Candidates are assessed on the basis of merit, competence, and qualifications without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law.
- Salesforce uses artificial intelligence tools to help recruiters assess and evaluate candidates' resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions.
- Reasonable accommodations are available during the application and recruiting process via the Accommodations Request Form.