SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Perk (formerly TravelPerk) is an intelligent platform for travel and spend management trusted by 12,000+ companies worldwide. The company automates manual work across travel bookings, expenses, invoice processing, and more, addressing the $1.7 trillion problem of shadow work that wastes 7 hours per employee weekly.
The AI Systems Analyst is a senior individual contributor and technical authority on agentic AI within the Revenue Systems team. This role sits at the center of Perk's AI infrastructure transformation, responsible for building production-grade, multi-step agent systems that replace real manual work in how Sales and GTM operate. Unlike experimental LLM work, this position focuses on deployed systems with real dependencies and users.
Key Responsibilities:
Agentic Workflow Design & Build: Design, build, and maintain multi-step AI agents using Python and LLM APIs (Claude, OpenAI) that automate research, qualification, routing, and decision-making across the revenue stack. Architect robust production systems with clear error handling, observability, and graceful degradation. Build a reusable agent framework with shared abstractions, tooling patterns, and integration modules that enable the broader Revenue Systems and GTM Engineering team to ship AI workflows efficiently. Evaluate and integrate emerging agentic tooling and patterns with well-reasoned recommendations on build vs. buy decisions.
Data Pipelines & Systems Integration: Build and maintain data pipelines connecting Salesforce, outbound tools, enrichment providers, and internal systems. Engineer API integrations, webhook-driven triggers, and event-based flows using Python, Make, and equivalent automation tooling. Own the data layer underpinning AI decision-making through schema design, data quality maintenance, and monitoring logic. Integrate deeply with Salesforce including custom objects, flows, and automation to ensure agent outputs are accurately reflected in the CRM.
Sales & GTM Team Enablement: Partner with GTM leadership to identify where manual effort can be replaced by intelligent automation, from account research and signal triage to follow-up sequencing and CRM hygiene. Translate business problems into scoped, shippable agent systems with realistic timelines and trade-offs. Build tooling and interfaces giving non-technical teams visibility into agent activity and confidence in outputs. Rapidly diagnose and resolve production system failures to minimize disruption to selling time.
Technical Standards & Team Leverage: Set and maintain engineering standards for AI systems within Revenue Systems including version control, documentation, testing patterns, and deployment hygiene. Share frameworks, code, and learnings with the broader GTM Engineering team. Provide feedback to inform roadmap prioritization, surfacing where automation works, where it is brittle, and where human judgment still wins.
The 12-month goal is building a reusable agent framework that the broader team builds on top of, requiring strong engineering instincts alongside business judgment. The role reports to the Senior Manager, Revenue Systems, and works closely with GTM Engineering and Sales leadership. This is a highly visible position with direct line of sight to commercial outcomes.
Perk operates with an IRL-first approach, requiring 3 days per week in-office at one of their hubs. The company offers relocation support for candidates from anywhere in the world. English is the official office language.
Requirements:
Must-Have:
- 5+ years in a technical role building production systems (GTM Engineering, Revenue Systems, or software engineering with strong GTM exposure in B2B SaaS)
- Hands-on experience building multi-step AI agents using Python and LLM APIs (Claude, OpenAI, or equivalent) in production context—deployed systems with real dependencies and users, not just prompt experimentation
- Strong Python engineering fundamentals: clean, maintainable, testable code with clear distinction between working prototypes and reliable systems
- Direct experience integrating APIs, webhooks, and event-driven flows using automation tooling (Make, n8n, Zapier, or equivalent) alongside custom Python solutions
- Salesforce proficiency at configuration layer: custom objects, flows, reporting, and data integrity logic
- Track record translating ambiguous business problems into scoped, delivered technical solutions with ability to size problems, push back on unrealistic scope, and ship
- Strong instincts for system design: building observable, recoverable systems that do not create maintenance debt
Strong Advantage:
- Experience designing agent frameworks or shared infrastructure patterns for other developers
- Familiarity with GTM tooling landscape (Clay, Outreach, Gong, Apollo) and connecting agent outputs into that stack
- Exposure to conversation intelligence platforms (Gong or equivalent) and using call data as input to automated workflows
- Experience in high-growth SaaS environments where stack evolves and priorities shift quickly
- Prior work on signal-based systems using hiring data, funding triggers, intent signals, or similar event streams as inputs to automated decision-making
