Lead GTM Data Operations Analyst, AI Workflows

Klaviyo
Boston, MA, United States
3 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$124,000.0 - $186,000.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Dictionary Data Integrity Python (Programming Language) Log Analysis Object-Oriented Software Development Performance Tuning DataOps Salesforce.Com Shell Script SQL Databases
+8 more
Data Streaming Large Language Models Snowflake Multi-Agent Systems Prompt Engineering Data Strategy Salesforce Object Query Language (SOQL) Automation Anywhere

Job description

GTM Data Strategy & Operations stood up from scratch with no predecessor. Today the function runs on three offshore contractors and zero FTEs, managed by a single leader who is simultaneously building the agentic infrastructure, operating it in production, and driving major initiatives (hierarchy redesign, data quality assessment, vendor optimization).

The operating model is deliberately agentic AI-first: a multi-agent pipeline (Cartographer, Sentinel, Resolver, Reporting) handles detection, enrichment, hierarchy mapping, and conflict resolution at scale. This is not a future-state vision, these agents are live and processing enterprise account families in production today.

The problem: one person cannot build, operate, and extend this system while also managing strategic workstreams. The function currently covers only core Tier-1 fields. Dozens of account, contact, and lead signals remain unaddressed. Every pipeline run, every failure diagnosis, and every offshore handoff flows through a single point of failure.

This role is the first onshore execution hire for an agent operator who can keep the system running, improve it, and extend detection and resolution coverage as GTM leadership prioritizes new data elements., * Run and monitor production pipeline sessions (Cartographer, Sentinel, Resolver) across scheduled cadences; diagnose and resolve failures (API errors, session timeouts, data anomalies) without escalating to the function lead.

  • Execute pipeline runs in Claude Claude and tmux; manage long-running batch processes; interpret logs and output to confirm data integrity before downstream handoff.
  • Maintain pipeline orchestration scripts and configuration; extend agent coverage as new data elements are prioritized by GTM leadership.

Agent Tuning & Improvement

  • Refine detection rules, prompt logic, and confidence thresholds based on output analysis and false-positive/negative patterns.
  • Evaluate agent accuracy by segment (Enterprise vs. MM/SMB) and recommend rule or workflow changes backed by evidence.
  • Run bake-offs (vendor vs. AI enrichment) to optimize cost, coverage, and accuracy; document results for decision-making.

Sentinel Offshore Resolution Loop

  • Own the handoff between Sentinel detection output and Concentrix triage queues; define queue structure, priority tiers, and resolution instructions.
  • Monitor offshore resolution quality and throughput; refine detection rules based on patterns surfaced through triage.
  • Close the feedback loop: track resolution outcomes back to agent configuration to reduce recurring false positives and improve detection precision., * Maintain ops-only staging fields; manage the promote-to-production flow with audit controls.
  • Design and run AI-assisted enrichment workflows (Clay + LLM prompts) with evidence links and confidence thresholds.
  • Monitor fill-rate, sampled accuracy, freshness, and cost-per-record by source and segment; surface vendor performance issues and recommend changes.
  • Keep data dictionaries, SOPs, and runbooks current as agents and processes evolve., * Scheduled pipeline runs execute without function-lead intervention; failure-to-resolution cycle time under 24 hours for non-blocking issues.
  • Agent coverage extended to new data elements as prioritized (measured by number of signals under active detection).

Detection & Resolution Quality

  • Sentinel detection precision and recall improve quarter over quarter, tracked by segment.
  • Concentrix resolution queue throughput and accuracy meet defined acceptance thresholds.
  • False-positive rate decreases through feedback-loop refinement.

Requirements

Do you have experience in Snowflake?, * 3-6 years in Data Ops, Sales Ops, or GTM Ops with hands-on data quality ownership for account and contact data.

  • Proficiency with Snowflake (SQL for querying, analysis, validation) and SFDC (object model, field configuration, data flows).
  • Working experience with Claude Code or comparable LLM-based tooling in an operational (not just experimental) context.
  • Experience designing and running AI-assisted enrichment workflows (e.g., Clay + LLM prompts) and evaluating accuracy/coverage.
  • Comfort operating in a command-line environment: tmux, shell scripts, log analysis, batch process monitoring.
  • Process design mindset with a bias toward measurable outcomes; strong written communication., * Experience with account/contact data vendors (D&B, ZoomInfo, Clearbit, StoreLeads) and waterfall enrichment logic.
  • Python for QA scripting, sampling, or light automation.
  • Familiarity with prompt engineering, confidence scoring, and AI guardrails (evidence capture, versioned prompts, QA sampling gates).

Tool Stack

  • Core: Snowflake (SQL), SFDC, Claude Code, Clay
  • Pipeline: Shell orchestration, Cartographer / Sentinel / Resolver agents
  • Enrichment: D&B, ZoomInfo, Clearbit, StoreLeads, LLM prompts
  • Nice to Have: Python, SOQL, prompt engineering frameworks
  • AI Guardrails (Expected Practice): Confidence floors, evidence capture, versioned prompts, 10% QA sampling gates, audit-on-promote, drift alerts, and privacy/compliance checks. This role is expected to uphold and improve these practices, not just follow them.

Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.

Benefits & conditions

3.83.8 out of 5 stars Boston, MA 02111 $124,000 - $186,000 a year, In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.

Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process. Base Pay Range For US Locations: $124,000-$186,000 USD

This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.

Get to Know Klaviyo

We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators-ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.

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