Staff AI Engineer - Revenue Operations
New
United StatesFull-TimeStaff
Salary174,986 - 209,983 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 8+ years of software engineering experience, 2+ years hands-on experience applying LLMs/AI to production workflows
- Required Skills
- Node.jsPythonGCPGitJavascriptSalesforceHubSpotBigQueryPrompt EngineeringLangChain
Requirements
- 8+ years of software engineering experience with depth in backend development, systems integration, or data/analytics engineering
- 2+ years hands-on experience applying LLMs/AI to production workflows, not just prototypes
- Strong proficiency in Python and JavaScript/Node.js
- Experience with Git-based workflows, code review practices, and testing discipline
- Hands-on experience with LLM frameworks and patterns including prompt engineering, RAG, function calling/tool use, structured output parsing, and evaluation
- Experience building and operating multi-agent systems at scale including agent decomposition, orchestration patterns, state management, and production monitoring
- Ability to diagnose business problems before writing code, thinking in workflows and outcomes
- Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services (Cloud Functions, Cloud Run)
- Understanding of LLM failure modes and production mitigations including confidence thresholds, fallback logic, human escalation, and cost/latency management
- Proven ability to identify high-leverage problems, push back on low-impact requests, and deliver end-to-end with minimal direction
- Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code)
- Clear technical communicator to both engineers and business stakeholders
- Familiarity with GTM platforms like Salesforce, HubSpot, Outreach, Gainsight, or similar CRM/sales engagement tools
Responsibilities
- Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation
- Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP, or similar) that operate 24/7 across teams
- Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps, CLIs)
- Implement observability and feedback loops including logging, performance metrics, prompt iteration, model evaluation, and cost management
- Establish governance and compliance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation paths
- Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems (BigQuery, Slack, Salesforce, email, calendars, analytics tools)
- Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal knowledge bases, customer data, and real-time business context
- Build serverless or containerized services (GCP Cloud Functions, Cloud Run) that scale with usage and integrate with Grafana's cloud infrastructure
- Partner with RevOps, and Finance to build solutions with measurable business outcomes
- Design and deploy workflows using orchestration tools (n8n, Workato, or custom platforms) with CI/CD, testing, and production reliability standards
- Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently
View Full Description & ApplyYou'll be redirected to the employer's site
