Senior Forward Deployed Engineer

Salesforce; Germany (OH); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical Care

Life Insurance

Retirement Savings

Employee Assistance Programs

13 paid days off annually

Job summary

Salesforce is seeking a Senior Forward Deployed Engineer responsible for delivering complex AI solutions within enterprise customer environments. In this role, you will mentor engineers, lead technical delivery, and ensure that deployments meet top engineering standards.

Successful candidates will have 6+ years of experience in software engineering, a degree in Computer Science, and fluency in both German and English. Additional benefits include medical care, life insurance, and 13 paid holidays annually.

Qualifications

• 6+ years of software engineering or technical delivery experience.
• Integrated LLMs into production with frameworks like LangChain.
• Communication skills to engage effectively with peers and stakeholders.

Responsibilities

• Lead technical delivery and mentor team members in engineering standards.
• Own end-to-end build and deployment of agentic AI solutions.
• Surface customer insights directly to Product and Engineering.

Skills

Salesforce certifications (Administrator, Platform Developer I/II, Agentforce Specialist, System Architect)

Experience architecting multi-cloud, multi-system enterprise AI solutions for Global 500 customers

Deep experience in data modeling, processing, and analytics

Mentorship experience in technical talent

Fluent in German and English

Education

Degree in Computer Science or a related field

Tools

Salesforce Data 360

Snowflake

Databricks

Python

JavaScript/TypeScript

Java

Apex

Job description

• 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
• Your passion for well-crafted software that solves real problems will be supported by best-in-class AI tools and a team of talented builders around you
• Technical Ownership: 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 AIproduct 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
• 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. These problems are routed to you because of your track record of solving them
• 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

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year

Qualifications

• Salesforce certifications (Administrator, Platform Developer I/II, Agentforce Specialist, System Architect)
• Experience architecting multi-cloud, multi-system enterprise AI solutions for Global 500 customers
• Familiarity with DevOps/CI-CD practices, observability tooling, or data governance frameworks
• Track record of influencing enterprise software product roadmaps through field engineering insight
• Actively tinker with the evolving AI/data landscape — piloting new tools, experimenting with new models, and staying genuinely curious about what’s coming next
• 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
• 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
• Integrated LLMs into production, used frameworks like LangChain or LlamaIndex, and applied prompt engineering and responsible AI practices in real customer contexts
• Communicate clearly and credibly with engineering peers, customer architects, and executive stakeholders
• Mentored technical talent and created reusable assets — frameworks, playbooks, internal tooling
• Expert in at least one of Python, JavaScript/TypeScript, Java, or Apex, and conversant in the others
• Fluent in German and English
• Entrepreneurial, get-things-done mindset focused on fast, impactful delivery — and the judgment to know when “fast” is the wrong call
• Architectural judgment expected; technical depth required
• Degree in Computer Science or a related field
• Open-source contributions, published technical writing, or conference presentations