---
title: 'Software Engineer, Applied AI at Clay Labs'
canonical: 'https://feeny.ai/job/software-engineer-applied-ai-clay-labs-new-york-pa00r2bzbtqv'
type: 'job'
last_seen: '2026-09-11'
---

# Software Engineer, Applied AI at Clay Labs

- **Company:** [Clay Labs](https://feeny.ai/companies/clay-labs)
- **Location:** New York, NY
- **Compensation:** $170k–$300k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-14
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/claylabs/5e07db20-d96a-4dff-b7d3-3bf1cdde6fc1

## Job description

## About Clay

AI is unleashing the biggest wave of company creation in history. Clay's mission is to be the engine those companies use to grow to their full potential. Clay predicts the next best action for your business and then helps you take it. We started by aggregating the best data for B2B companies. Then, we built the infrastructure to run any personalized campaign on top of it, including emails, ads, landing pages, and workflows that make reps more productive. Now, we're building agents that can help grow your company for you. We're already helping thousands of customers — including Anthropic, OpenAI, Google, and Visa — go to market with unique data, signals, and AI research. In 2026, we raised a [$115M Series D](https://www.linkedin.com/safety/go/?url=https%3A%2F%2Fwww.nytimes.com%2F2026%2F09%2F09%2Fbusiness%2Fdealbook%2Fclay-ai-fundraising.html%3Fsmid%3Durl-share%26unlocked_article_code%3D1._1A.E5rN.MeYsbgEsUKbB&urlhash=XS4q&mt=4bpSf4a8omAKuAHqAqZx6C11QpbLK_QwIhSV7gSf4Wf9aywPF_KBSiX9IkWE1AhXBEjPH8mK6fAEN7CMFlpvo0lPAtKRjs-dhgzYqHiVKUMCRtw0jScFgxWCRRfYs4HCX0YL9L6PCQz-edBLinvRdU_TaVUL2dA3&isSdui=true&lipi=urn%3Ali%3Apage%3Ad_flagship3_feed%3BoQmIsufoRJm7X2HC5Rqd%2Fw%3D%3D) at $7.1B Valuation led by Wellington — and are on track to cross $200M in revenue this quarter. We also launched a $1M Scholarship fund for GTME Education. Some things to know about us:

- Our [community](http://community.clay.com) includes 17,000+ customers, 200+ integration partners, 125+ agencies, 50+ [Clay clubs](https://luma.com/claylive), and 30k members on Slack.
- Our [culture](https://nextplayso.substack.com/p/spotlight-clay) is unique inside and outside of work. Our team members are also DJs, activists, writers, clowns, marathoners, skydivers, psychedelic therapists, social workers, and more.
- All employees can work with world-class coaches who specialize in creativity, management, and more.
- Our operating principles — including negative maintenance and non-attached action — guide our work. Read more about them [here](https://cdn.prod.website-files.com/61477f2c24a826836f969afe/685d83a71452245cc1129791_4d770abfd83e276ec15315a2e06945bd_Clay2025_OperatingPrinciples.pdf).
- Read about us in the [NYT](https://www.nytimes.com/2025/08/05/business/dealbook/clay-ai-marketing-fundraise.html), [Forbes](http://google.com/search?q=forbes+clay&rlz=1C5OZZY_enUS1155US1155&oq=forbes+clay&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQABiABDIHCAIQABiABDIHCAMQABiABDIHCAQQABiABDIHCAUQABiABDIHCAYQABiABDIHCAcQABiABDIHCAgQABiABDIHCAkQABiABNIBBzkzM2owajSoAgOwAgHxBVAe8UAxJx_p&sourceid=chrome&ie=UTF-8), [First Round Review](https://review.firstround.com/podcast/inside-clays-unconventional-path-to-1-25b/), [and more](https://www.clay.com/press).

Hear from our employees directly on our [Glassdoor](https://www.glassdoor.com/Overview/Working-at-Clay-EI_IE9850794.11,15.htm) page!

## About the Team

Clay's product is increasingly powered by AI agents — systems that research, enrich, and take action on behalf of our users, not just generate text. These aren't lightweight copilots layered onto an existing product; they're long-horizon agents built to take on the kind of multi-step, judgment-heavy work that skilled GTM teams spend real time on today. Several teams are working on different layers of this: agents that execute real go-to-market workflows end-to-end, and the shared platform (harness, memory, tools, retrieval, evals) that those agents run on. This role is a shared entry point across those teams. Depending on your background and interests, you'll be matched to a specific team as you move through the process - but every team here is working on the same underlying problem: closing the gap between an agent that looks good in a demo and one that's dependable enough to run unattended in production.

## About the Role

You'll work closely with product, research-adjacent teammates, and other engineers to make sure agents aren't just capable, but reliable, steerable, and worth trusting with real work. That means the job isn't only about improving model behavior in isolation - it's about turning those improvements into measurable gains in task completion, reliability, and time saved for the people using them.

## What You'll Do

Depending on the team, you might work on: Agent products

- Design and iterate on agent behavior across real GTM workflows. For example, sourcing a Total Addressable Market (TAM) list, which in practice means navigating ambiguous Ideal Customer Profile (ICP) definitions, reconciling conflicting signals across data sources, and making judgment calls that experienced analysts spend real time on.
- Map manual, multi-step workflows that GTM teams do today and turn them into agent-driven flows that are as good as, or better than, a human doing it by hand.
- Build and run evals that measure whether an agent actually completed the task correctly - not just whether the output looked plausible - and use them to catch regressions and failure modes.
- Analyze real failures in production and systematically improve robustness.
- Work with product to take agent flows from early prototype through closed beta and into general availability, and help define what "good" looks like for each one.

Agent platform & infrastructure

- Build the core agent harness that other teams build on top of, including memory systems, tool infrastructure, and retrieval architecture
- Improve agent performance through prompting strategies, tool-use design, and context construction
- Design guardrails and safety checks so agents behave predictably in production
- Build a cross-surface evals framework so every team building on the platform can measure quality, regressions, and performance the same way
- Build feedback loops that turn real usage and production logs into better prompts, tools, and eval coverage over time
- Support teams building their own forks or variants of the managed agent for their specific use case

## What You'll Bring

- Experience building or shipping production systems with LLMs or agents. This might look like multi-step agent orchestration, prompting and tool-use design, retrieval, structured extraction, or fine-tuning.
- Strong backend fundamentals in APIs, databases, distributed systems.
- Experience with model or agent evaluation: designing evals, measuring regressions, or turning fuzzy quality questions into measurable signals
- A systems-and-outcomes mindset. You care about whether the product actually works for users, not just about model metrics in isolation
- Comfort debugging messy, real-world failures and a bias toward shipping and iterating quickly in a space where best practices are still being figured out

Nice to Haves

- Experience with agent frameworks, tool-calling systems, or retrieval architectures (vector search, hybrid search, RAG)
- Experience building or maintaining eval/benchmark infrastructure for LLM-based systems, or running fine-tuning in production
- Experience with GTM, sales, or marketing workflows (e.g. lead sourcing, enrichment, audience building)
- Familiarity with Clay's stack: React, TypeScript, Python, AWS (Aurora/Postgres, ECS/Fargate, Lambda, OpenSearch, Clickhouse, Elasticache/Redis), Terraform, Datadog
- A growth mindset - we're building a team that's curious, open-minded, and happy to invest in each other's learning, not just their own

## About Clay Labs

## Company Overview
- **One-liner**: Clay is a creative go-to-market (GTM) platform that helps teams build automated systems to grow revenue by combining data enrichment, AI agents, and workflow orchestration.
- **Entity Type**: Private (Series C expansion at $3.1B valuation, tender offer at $5B)
- **Headquarters**: New York, New York, United States
- **Founded**: 2017
- **Founders**: Not publicly disclosed in available sources

## Core Business
- **Primary industry**: Go-to-market (GTM) software / Sales & Marketing technology
- **Target customers**: B2B GTM teams of all sizes – from solo operators to enterprise sales, marketing, and revenue teams
- **Mission**: Help people grow businesses by providing the best data foundation possible to reach their best-fit customers

## Products & Services
- **Data Marketplace**: Access to 200+ data and AI vendors in one contract – enabling teams to buy, enrich, and combine first-party, intent, and third-party data.
- **Agents**: Create AI agents that mimic top sales representatives to automate research, prep, and follow-ups.
- **Orchestration**: Build multi-step workflows that connect GTM tools (CRM, email, ads) and trigger actions based on real-time signals.
- **Automated Outbound**: Programmatically generate 1:1 messaging, launch new plays in days, and scale outbound campaigns.
- **Lead Scoring & Routing**: Enrich, score, and route every lead to the right rep in minutes.
- **Pre‑Call Prep Agent**: Researches prospect bios, earnings reports, and company changes to fully automate pre‑call prep.

## Market Standing
- **Valuation**: $5B (via employee tender offer, January 2026); previous Series C at $3.1B (2025)
- **Key Metric**: Annual revenue of $35.5M; total funding $202M
- **Notable Investors**: Sequoia Capital, CapitalG, First Round Capital, Meritech Capital Partners
- **Growth Signals**:
  - Headcount of 792 employees (+74.6% YoY)
  - 500,000+ GTM teams trust Clay
  - Named #1 mid-stage company on the ENT30 list
  - Only GTM company on Forbes’ 2025 AI 50 List
  - Customer case studies: Anthropic 3× enrichment rate, OpenAI automated pre‑call prep, Intercom grew outbound pipeline 140%, Vanta cut follow‑up time from 3 days to <1, Mistral AI cut TAM mapping from 2 months to 10 days
  - Active job postings grew 763% YoY; operates in 47 countries

## Competitive Advantages
- **Unique combination of data marketplace + AI agents + workflow automation** in a single platform – reduces the need for multiple tools and manual coordination.
- “A single person can run growth campaigns that previously required coordinating the entire GTM team.”
- **Massive data marketplace** (200+ vendors) with one contract simplifies data procurement.
- **Network effects** – 500,000+ users contribute to a growing community of GTM engineers.

## Strategic Focus
- Deepen AI capabilities in agentic workflows for GTM
- Expand the data marketplace with more vendors and intent signals
- Continue scaling globally (already in 47 countries) and hiring aggressively (164 open roles)
- Build out ecosystem partnerships and enable customers to become “GTM engineers”

## Why Work Here
- **Culture**: Kindness, creativity, “quiet ego”, and a focus on helping each other grow. Values like “Make it work, then make it great” and “Negative maintenance” (improve a little every day).
- **Work model**: Flexible in‑person culture – office in Chelsea, NYC, with daily team lunches and DJ Fridays. Hybrid flexibility offered; remote roles available.
- **Benefits**: Competitive salary, fully funded health/dental/vision, 4 months paid parental leave, IVF and egg freezing benefits, flexible PTO, yearly company retreats, visa sponsorship.
- **Engineering**: Emphasis on craft, attention to detail, and deep enjoyment of the building process. Engineers work on AI, data infrastructure, and scalable systems.
- **Interview process**: Typically 3–5 interviews (behavioral + technical) plus a founders interview; practical exercises and reference checks.

## Sources
1. [Clay.com – Careers](https://www.clay.com/careers)
2. [Clay.com – About](https://www.clay.com/about)
3. [Clay.com – Main Site](https://www.clay.com/)
4. [LinkedIn – Clay (Clay Labs Inc.)](https://www.linkedin.com/company/grow-with-clay)

## Other roles at Clay Labs

- [VC Partnerships](https://feeny.ai/job/vc-partnerships-clay-labs-new-york-cdbmm6w3j5a8) — New York, NY
- [Technical Partnerships Solutions](https://feeny.ai/job/technical-partnerships-solutions-clay-labs-new-york-0nwkxyyf5p6v) — New York, NY
- [Account Executive (GTME - Strategic)](https://feeny.ai/job/account-executive-gtme-strategic-clay-labs-london-9ahf5g013nrp) — London, United Kingdom
- [GTM Engineer Manager - Seller Efficiency](https://feeny.ai/job/gtm-engineer-manager-seller-efficiency-clay-labs-new-york-vyep1se8jjfk) — New York, NY
- [Account Executive (GTME - Top Accounts/Strategic)](https://feeny.ai/job/account-executive-gtme-top-accounts-strategic-clay-labs-san-francisco-1g5zagt7mv97) — San Francisco, CA
- [IT Operations Engineer](https://feeny.ai/job/it-operations-engineer-clay-labs-new-york-7pp5p4m62x5c) — New York, NY
- [IT Support Engineer](https://feeny.ai/job/it-support-engineer-clay-labs-new-york-7jvs9kdjhfq4) — New York, NY
- [Data Science & Analytics Manager](https://feeny.ai/job/data-science-analytics-manager-clay-labs-new-york-2rbhz07mxk6c) — New York, NY
- [Account Executive (GTME - New Business)](https://feeny.ai/job/account-executive-gtme-new-business-clay-labs-new-york-ddcad8y0kkjk) — New York, NY
- [Growth, Adoption](https://feeny.ai/job/growth-adoption-clay-labs-san-francisco-rgax5d36358k) — San Francisco, CA