Technical Support Engineer II

CloudZero; Boston (MA); On-site; USD 90,000 - 130,000; Full time

Job summary

CloudZero's Technical Support team bridges customers with software developers, focusing on technically solving issues with AI assistance. You will dive into logs, queries, APIs, and data pipelines to trace how AI-spend and cloud-cost data move through our platform and determine why results look off.

The role is both a technical problem-solver and a customer-facing advocate, requiring calm, curiosity, and fast iteration while escalating to engineering only when necessary.

Qualifications

• 3–5 years in a complex troubleshooting environment, at the application and data level.
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Responsibilities

• Own and resolve complex technical tickets end to end across APIs, logs, databases, and data pipelines.
• Prioritize live ticket backlog by impact and communicate clearly with engineering or customers.
• Decide the right path for each issue: direct resolution, route to Customer Success, or escalate to engineering.
• Investigate health of cloud-billing connections across providers to ensure data is arriving as expected.
• Build knowledge content for AI deflection: docs, runbooks, guides for faster resolution.
• Utilize and improve AI tooling to troubleshoot and tune AI agents.

Skills

Problem-solving

Customer-focused

Ambiguity tolerance

Diagnostic instincts

SQL proficiency

Log analysis

AI tooling fluency

Cloud billing understanding

Communication

REST API fluency

Support platforms experience

AI workflow building

Tools

Snowflake

Sumo Logic

Intercom

Zendesk

Pylon

DevRev

Claude Code

Codex

Job description

About the Role

CloudZero's Technical Support team is the bridge between our customers and software developers, where the hard problems land after our AI frontline (Fin) deflects the routine. This is a technical problem-solving role first and a customer-facing role second.

You'll leverage AI to dive deep into logs, queries, APIs, and data pipelines, tracing how a customer's AI-spend and cloud-cost data moves through our platform and working out why something looks wrong.

Most of our stack is bespoke, so we'll teach you the product, but you need to arrive a strong, curious troubleshooter comfortable with ambiguity who thinks on your feet. We comprehend and resolve hard problems ourselves, escalating to engineering only when necessary. We're accelerating problem-solving, trading 'old support' for speed.

What You'll Do

• Own and resolve complex technical tickets end to end. Trace issues across APIs, logs, databases, and the pipeline that moves customer AI-spend and cloud-cost data through CloudZero, and resolve them without engineering when possible.

• Work a live ticket backlog, prioritize by impact, and drive clear communication whether with engineering or with customers.

• Decide the right path for each issue: resolve directly, route contracts and renewals to Customer Success, elevate to engineering.

• Investigate the health of customer cloud-billing connections across cloud providers: how they're set up, what data should arrive and when, and what 'healthy' looks like.

• Build the knowledge content that powers AI deflection: docs, runbooks, and guides that let Fin and our internal AI tooling deflect, accelerate, and resolve issues before they reach a person.

• Use and sharpen our AI tooling to troubleshoot faster, including helping tune Fin's AI agent to handle more on its own.

What You Bring

• A strong technical foundation and problem-solving mindset, a real drive to help customers, and an ability to remain calm in ambiguity.

• 3-5 years in a complex troubleshooting environment, at the application and data level (this isn't an infrastructure-operations role).

• Sharp diagnostic instincts: you reason from APIs, logs, and data flow to a root cause.

• Working SQL: you read and write queries against complex data (Snowflake or similar) comfortably. More than basic, short of expert.

• Log-analysis fluency, including from the command line (Sumo Logic, Snowflake, or comparable).

• Day-to-day fluency with agentic AI tools (Claude Code, Codex, or similar), and the judgment to catch when the AI is wrong before it reaches a customer.

• Enough understanding of cloud infrastructure to reason about billing and cost data: where it comes from, how it flows, and what it should look like coming back.

• Clear, confident written and verbal communication with customers.

• Experience with customer support platforms. Fin (formerly Intercom) preferred; Zendesk, Pylon, and DevRev comparable. Experience optimizing Fin or Intercom is a plus, as is building your own tooling or improving ours to optimize Fin's AI agent.

• REST API fluency (Intercom, Atlassian, and similar).

• A habit of building reusable AI workflows, authoring skills and prompts that turn a solved problem into a repeatable asset.

Nice to Have

• Hands-on exposure to multi-cloud billing or cost data (AWS, Azure, GCP, OCI)

• Deeper AI-operations experience, including permission scoping, plugin distribution, and curating known agent failure modes