Lead Salesforce Developer

๐Ÿข ServiceTitan ยท all ServiceTitan jobs
๐Ÿ“ United States
๐Ÿ’ฐ USD 152,600 - 229,000 / annual
๐Ÿ“… Posted 2026-08-14 ยท via Himalayas
๐Ÿท Salesforce-Developer,Salesforce-Architect,AI-Engineer,CRM-Developer,Salesforce-Development-Lead,Salesforce-Developer-Lead,Lead-Salesforce-Engineer,Senior-Salesforce-Technical-Lead,Salesforce-Technical-Lead,Salesforce-Lead-Engineer,Salesforce-Technology-Lead,Developer
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Ready to be a Titan?

ServiceTitan is looking for a Lead Salesforce Engineer to join our team. In this role, you'll own the architecture, development, and ongoing evolution of our Salesforce platform โ€” with a deep focus on CPQ and Billing โ€” while collaborating with stakeholders across Sales, Revenue Operations, and Engineering. You'll leverage AI tools to accelerate delivery, raise quality, and push the boundaries of what our Salesforce org can do.
What You'll Do

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Partner directly with Marketing, Sales, SDR, RevOps, and GTM Systems leaders to identify, prioritize, and define high-value AI use cases.

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Translate business problems into scalable technical solutions rather than simply implementing predefined requirements.

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Own solution delivery from discovery, technical design, and prototyping through production deployment, adoption, monitoring, and optimization.

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Design and build production-grade applications using Python, Azure, Salesforce, LLMs, RAG architectures, APIs, and third-party AI tools.

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Design reusable agentic solutions spanning orchestration, MCP servers and connectors, live system tool calling, conversational experiences across Slack, embedded chat, APIs, and Salesforce, with standardized connector libraries, deployment patterns, and Dev, UAT, and Production promotion paths.

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Develop AI solutions for:

- Account and prospect research

- Lead qualification and prioritization

- Personalized seller and SDR outreach

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Seller productivity and workflow automation

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Opportunity intelligence and next-best actions

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Pipeline inspection and deal-risk identification

- Forecast management and accuracy

- Guided selling and knowledge retrieval

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Integrate AI capabilities into Salesforce and the broader GTM technology ecosystem through APIs, platform events, automation, and embedded user experiences.

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Establish evaluation practices for AI quality, groundedness, relevance, task completion, hallucination risk, latency, cost, reliability, and business impact.

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Implement appropriate security, access, privacy, monitoring, and responsible-AI controls.

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Evaluate Salesforce-native, Azure-native, and third-party AI solutions and recommend whether to buy, build, or integrate.

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Convert successful solutions into reusable services, components, templates, evaluation datasets, and architecture patterns.

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Lead technical design and code reviews, mentor engineers, and help establish engineering standards for GTM AI solutions.

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Partner with business teams to drive workflow redesign, adoption, and measurable business outcomes.

What We're Looking For

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Typically 10+ years of software engineering, solutions engineering, systems engineering, or technical architecture experience.

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Experience building AI-powered solutions for Sales, SDR, Revenue Operations, or pre-sales organizations.

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Demonstrated experience designing, building, and operating production applications using Salesforce, Integration platforms, Python and Microsoft Azure.

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Strong hands-on experience with LLM-based applications, RAG, embeddings, vector or hybrid retrieval, prompt and context management, structured outputs, tool calling, and AI evaluation.

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Strong Salesforce expertise, including Salesforce Apex, Flow, Lightning Web Components, Platform Events, data models, APIs, integrations, automation, security, and custom development.

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Experience integrating Salesforce with cloud services, enterprise data sources, and third-party platforms.

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Deep functional understanding of GTM processes, including:

- Sales development and prospecting

- Lead and account management

- Opportunity lifecycle

- Pipeline generation and inspection

- Deal progression

- Forecast management

- Sales productivity

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Experience building production APIs, services, integrations, and data-processing workflows.

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Strong understanding of cloud security, identity, access management, data privacy, observability, testing, and deployment practices.

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