GTM Systems & AI Engineer, Confluent
$133.6-157k
+ Equity
Data streaming platform
Be an early applicant
Data streaming platform
1001+ employees
Be an early applicant
$133.6-157k
+ Equity
1001+ employees
Company mission
To help every organization harness data in motion so they can compete and thrive in the modern world.
Role
Who you are
- 3 to 7+ years in Revenue Operations, GTM Systems, Sales Ops, CS Ops, Business Systems, or similar roles improving GTM execution through process, systems, and automation
- A pattern of taking ambiguous GTM problems, getting to the root cause fast, and shipping improvements that teams actually adopt
- Strong judgment and follow-through: you surface tradeoffs early, close open loops, and keep work moving from idea to rollout to iteration
- Comfort with the technical basics that power modern GTM automation, including APIs/webhooks, JSON payloads, and SQL for validation or analysis (BigQuery preferred)
- Salesforce fluency and comfort working across pipeline, lifecycle, and post-sales workflows
- What Gives You an Edge:
- Hands-on experience with Relevance AI, Momentum, Clay, Gemini, or Claude
- Familiarity with GTM Systems like Salesloft, Zoominfo, Clari, D&B, DemandTools and common Sales and CSG workflows
- Experience building AI workflows with governance patterns (access controls, auditability, feedback loops)
What the job involves
- You’ll drive our shift to an AI-first GTM operating model across Sales and Customer Success. This role focuses on improving GTM execution by removing friction from the customer journey, from pipeline generation and deal execution through onboarding, adoption, expansion, and renewal
- You will take real workflow pain from the field and translate it into practical, measurable improvements using AI agents, automation, and better data flow across systems
- You’ll design and ship solutions using tools like Relevance AI, Momentum, Clay, and LLM tooling. You’ll influence GTM AI strategy by shipping what works, setting a high bar for quality and operational rigor, and creating reusable patterns that scale
- You’ll own outcomes end-to-end. That means turning ambiguous asks into a clear plan, making tradeoffs quickly, and shipping measurable improvements on a steady cadence. Act as the internal GTM AI Subject Matter Expert (SME), promoting responsible AI adoption and automation across GTM teams by recommending effective patterns, tooling, and best practices
- Own AI intake and delivery across Sales and CSG: run intake, clarify business problems, define requirements and success metrics, prioritize the backlog, and drive initiatives from 0 to 1 through release and iteration
- Build and ship AI workflows end-to-end: map current-state processes, identify friction, design future-state workflows, and implement agents and automations that teams can rely on day to day
- Partner cross-functionally to unblock delivery: work day-to-day with Sales, Customer Success, Marketing Ops, Business Technology, Data Science, Finance, and Legal to align on requirements, data usage, governance, and measurable outcomes
- Build with guardrails: embed permissioning, auditability, and compliance requirements into workflows from day one
- Launch what you build: drive rollout with lightweight enablement (training assets, office hours, comms), gather feedback, and continuously improve workflows after release
- Own quality and operational rigor: create test plans, run QA, manage prompt and workflow versioning, and maintain documentation, runbooks, and release notes so delivery is safe and repeatable
- Measure impact and iterate: track adoption and performance, validate results in partnership with Ops and Analytics, and continuously improve workflows based on usage and outcomes
Our take
Confluent is a commercial company built on top of the open-source Apache Kafka project. Confluent and Kafka have developed a streaming data technology that processes massive amounts of information in real-time. The streaming database technology was developed at LinkedIn as a way of moving massive amounts of messages. The company decided to open-source that tech in 2011, and Confluent launched as the commercial arm in 2014.
While the base open-source component remains available for free download, it doesn’t include the additional tooling the company has built to make it easier for enterprises to use Kafka. Confluent's value add is in those additional tools, including a cloud version of the product and a marketplace for sharing extensions to the platform.
Confluent expanded strategic partnerships with Microsoft and acquired Immerok, and in 2023 expanded its cloud platform. 2024 saw further product expansions with the launch of the Confluent Migration Accelerator, all exemplifying how the company is living up to its name by rocket-boosting the benefits of Apache Kafka integration for companies.
Now, it looks like IBM is eyeing the company for acquisition and Confluent looks to be a natural fit. Long positioned as the real-time backbone behind modern application, Confluent would gain global scale and an even deeper enterprise reach under iBM, while cementing its role at the center of AI-driven architectures. For COnfluent, the deal would marka shift from fast-growing independent disruptor to foundational infrastructure player powering the next wave of enterprise AI.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Apr 2020
$250m
SERIES E
Jan 2019
$125m
SERIES D
Total funding: $455.9m
Company HQ
Old Mountain View, Mountain View, CA
Leadership
Jay Kreps
(Co-Founder & CEO)Prior to co-founding Confluent in 2014, Jay spent 7 years at LinkedIn, holding various roles including Principal Engineer and Principal Staff Engineer.
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