Senior Forward Deployed Engineer

About the Role

Technical depth required.

Architectural judgment expected.

Salesforce is hiring Senior Forward Deployed Engineers — the Technical Builders, responsible for deciding that leads who design, build, and deploy the most complex agentic AI solutions directly inside enterprise customer environments.

You'll lead technical delivery on your team, mentor the next wave of engineers, and set the engineering standards that define how agentic AI gets deployed at scale.

Partnering closely with a Deployment Strategist (Strategic Builder - a customer-facing advisor who shapes AI strategy and drives adoption), you'll own outcomes end-to-end, from architecture decision to production.

Key Responsibilities

• Partner with a Deployment Strategist to own customer outcomes end-to-end.

You're the senior technical authority in the room, ensuring deliverables meet the highest engineering standards, whether it was generated by an AI tool by a colleague or written by you directly.

• AI-Supported

Engineering: Cursor, Claude, and Salesforce coding products like Vibes are embedded in your daily workflow.

The conventions and patterns you develop tend to propagate through the team because other Builders look to your work as reference.

• Roadmap

Influence: Your field experience routes directly to Product and Engineering.

The gaps you hit and the edge cases you encounter in real life customer environments become the features they ship.

Senior Forward Deployed Engineers are the most credible voice in agentic AI product evolution.

• Continuous

Innovation: You're expected to stay at the forefront — piloting emerging AI tools, experimenting with new models and frameworks, and sharing what you learn with your team and customers.

• What You'll Actually Be Building
• 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: agent logic, tool calls, multi-agent orchestration, deterministic guardrails, and the integration patterns that hold up in enterprise environments.
• Your reference implementations become the basis for how other Builders approach similar problems.
• Own the data lifecycle: model design, processing pipelines, and data readiness for AI applications across Salesforce Data 360, Snowflake, Databricks, and customer-specific platforms.
• Resolve the technical blockers that other engineers can't — data integration failures, model deployment issues, orchestration breakdowns, performance regressions.
• Build and maintain agent performance dashboards and customer KPI reporting to track deployment health and business outcomes across engagements.
• 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.
• 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 org draws from.
• Mentor other Engineers through code reviews, pair sessions, and shared work. Most of your influence on developing engineers happens inside the same codebases you're building in.
• Provide technical depth on at-risk or strategically critical deployments when senior engineering judgment is needed.
• Surface field insights directly to Product and Engineering.

The gaps and edge cases you encounter in real customer environments are some of the most valuable inputs to the Agentforce roadmap.

• Partner with the Deployment Strategist on your team to translate complex customer business challenges into agentic solutions that actually ship.

Qualifications

• Fluent in German and English.
• 6+ years of software engineering or technical delivery experience, with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or Saa S environments.
• Degree in Computer Science or a related field.
• Expertise in at least one of Python, Java Script/Type Script, Java, or Apex, and conversant in the others.
• Integrated LLMs into production, used frameworks like Lang Chain or Llama Index, 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: Agentforce, Apex, LWC, Flows, and Salesforce APIs.
• Entrepreneurial, get-things-done mindset focused on fast, impactful delivery — and the judgment to know when "fast" is the wrong call.
• Mentored technical talent and created reusable assets — frameworks, playbooks, internal tooling.
• Communicates clearly and credibly with engineering peers, customer architects, and executive stakeholders.
• Actively tinker with the evolving AI/data landscape — piloting new tools, experimenting with new models, and staying genuinely curious about what's coming next.
• Excited to travel ~25% of the time, embedded with customer engineers.
• Nice-to-Haves
• Salesforce certifications (Administrator, Platform Developer I/II, Agentforce Specialist, System Architect).
• Familiarity with Dev Ops/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.

Any employee or potential employee will be 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.

This policy applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination and everything in between.

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