Build the tools that give agents go-to-market superpowers.

Deepline | In-Person | NYC Figure out what’s uniquely difficult about our customers' problems, and ensure Deepline solves it. That's it. Deepline gives AI agents the ability to enrich, validate, deduplicate, and sequence across 40+ GTM providers with a single command. The technology works. But at high-complexity enterprises, teams need an engineer in the room with the customer. You'd be ours. If you get a rush from building something live while a customer watches, and then seeing it actually work in production at scale, this is the job. Every week is different. Every customer has a different problem. You figure it out on the spot. What your first 90 days look like Month 1: You're embedded with two customers. You deploy Deepline into their CRM, enrichment stack, and sequencing tools. You help them customize their AI workflows to match their hardest problems. It’s a mix of data & product engineering. A signal-based trigger workflow for the other. Both go live before the month ends. You text the team when something clicks because you can't help it. Month 2: You join a sales call. The prospect describes an “unsolvable” problem. You build the solution live on the call. They watch enrichment cascade through providers, deduplicate against their CRM, and push contacts into Instantly. The deal closes that week. You create a reusable playbook from the deployment because we hate doing the same thing twice. Month 3: You've surfaced 3 product gaps from the field that nobody in the office would have found. Two become features. You've built trust with technical buyers by being the engineer who actually ships, not the one who "takes it back to the team." You've got opinions about where the product should go next. We want to hear them. What you'll own Deploying Deepline into customer environments. CRM, enrichment stack, sequencing tools, data warehouse. Custom workflows and integrations for customer-specific GTM challenges (ICP scoring, territory routing, signal triggers) Technical closing. Join sales calls, run live implementations, turn "interesting demo" into "production deployment" in days. Surfacing product gaps from the field. You'll have more roadmap influence than anyone outside the founding team. Reusable playbooks from successful deployments that become product features Building trust with technical buyers by shipping, not presenting You'll recognize yourself here You've done customer-facing technical work. Solutions engineering, sales engineering, professional services, consulting. And you loved it. You write production code ( Next.js , Python, TypeScript, SQL) and you can explain complex systems to a VP of Sales in plain language. Bias toward action. Customer has a problem? You fix it live. You don't file a ticket. You've worked with GTM tools (CRMs, enrichment providers, sequencing platforms) or enterprise data systems. Variety is the point. No two weeks look the same. That's what you want. You're the person who builds a prototype before the meeting where you were supposed to discuss whether to build a prototype. You want to be early enough to shape the product and the GTM motion from the inside. Compensation Salary: 140K-260K Equity: 0.25%-0.75% (seed-stage) Benefits: Health insurance, equipment budget, travel budget for on-site customer work Location: In-person, with travel to key customers (~25%)

Founding Full-Stack Engineer Location: New York City Type: Full-time ABOUT DEEPLINE Deepline is the operating system for GTM execution. We turn operator intent into governed execution and measurable outcomes. Not more dashboards. Not more automations. The backend for GTM engineering that makes your GTM stack actually work. Our vision is "ambient automation" that exists & solves problems before you know they exist. We're building the universal API for B2B businesses. Replace 20+ API calls to dozens of tools with a single call to Deepline's Context API. Deepline is a context manager that understands how the real-world works, with an intent compiler that turns context & natural language into outcomes with guardrails and observability. Team : Small senior team from Uber, Lyft, OM1, Capchase. MIT, Waterloo, Berkeley, Princeton, UCSD. Funding : $3.3M pre-seed from Lerer Hippeau, K5 Global, Exceptional Capital, Sabrina Hahn, Rohan Shah THE PROBLEM Every AI tool today hits the same wall: they can't reliably purchase access to proprietary data, your company's knowledge base, or what they don't already know how to get. Claude Code can't query your Snowflake out-of-the-box. ChatGPT doesn't know your weird custom Salesforce schema. They hallucinate because they lack structured context. The root cause: data infrastructure was built for humans, not AI agents reasoning about business context. Database access patterns are shifting. SQL won't be how AI systems query data in five years. 3 You'll build the structured context management layer that makes AI context selection reliable in production. This isn't better RAG or fine-tuning. This is inventing new data access patterns and context architectures that power the next generation of AI applications in the fastest changing space around. WHAT YOU'LL BUILD Context Management API Build the context layer AI systems need. Systems that maintain structured context across workflows, self-heal when data changes, and compound knowledge over time. New Data Access Patterns Design semantic query interfaces that replace SQL for AI agents. Build retrieval pipelines that reason about context before querying. Create systems that understand business semantics and go beyond data schemas. Self-Healing Data Models Architect feedback loops that automatically improve data models based on usage. Systems that detect when context breaks and fix it automatically. Knowledge graphs that evolve as the business evolves. Semantic Modeling Infrastructure Users need to be able to improve/expand their data model without data experts. Build the semantic layer that translates business questions & existing reports into precise, verifiable queries. Identity resolution across 50+ enterprise systems. Systems that learn customer language patterns and map them to business outcomes. WHAT WE'RE LOOKING FOR Required • 3+ years building production systems • Experience with retrieval systems, embeddings, vector databases, LLMs or knowledge graphs • Production ML experience: monitoring, versioning, evaluation frameworks • Experience with LLM orchestration (LangChain, LlamaIndex) and multi-agent systems • Familiarity with semantic layers (dbt), data warehouses (Snowflake, BigQuery), enterprise data systems Nice to Have • Enterprise data systems (Snowflake, BigQuery, Salesforce, Segment, Gong) • Multi-agent systems (LangGraph, CrewAI) or workflow orchestration (Airflow, Prefect) • Knowledge graphs, graph databases, semantic layer tools (dbt, Cube) • Real-time data pipelines and streaming architectures TECH STACK Core: Python (primary), TypeScript/JavaScript, SQL LLMs: Anthropic Claude API, OpenAI, in-house frameworks Knowledge Graphs/RAG Data Infrastructure: Snowflake/BigQuery/Redshift, dbt, Kafka/Pulsar, Reverse ETL (Hightouch, Census) Enterprise Integrations: Salesforce, HubSpot, Segment, Gong, Slack, Zendesk, Mixpanel/Amplitude COMPANY CONTEXT Stage: $3.3M pre-seed, proven product-market fit, growing adoption Team: Small senior team from Uber, Lyft, OM1, Capchase. MIT, Princeton, UCSD. You'll be engineer #5-6. Direct collaboration with founders & customers Culture: First-principles debate. Ship multiple times a day . Rapid iteration. In-person in NYC with quarterly off-sites. Compensation: $140K-220K base + meaningful equity. Early-stage upside in proven company. Jai, Saf, & Chirag Co-founders of Deepline

Founding GTM Engineer Location: New York City Type: Full-time ABOUT DEEPLINE Deepline is the operating system for GTM execution. We turn operator intent into governed execution and measurable outcomes. Not more dashboards. Not more automations. The backend for GTM engineering that makes your GTM stack actually work. Our vision is "ambient automation" that exists & solves problems before you know they exist. We're building the universal API for B2B businesses. Replace 20+ API calls to dozens of tools with a single call to Deepline's Context API. Deepline is a context manager that understands how the real-world works, with an intent compiler that turns context & natural language into outcomes with guardrails and observability. Team : Small senior team from Uber, Lyft, OM1, Capchase. MIT, Waterloo, Berkeley, Princeton, UCSD. Funding : $3.3M pre-seed from Lerer Hippeau, K5 Global, Exceptional Capital, Sabrina Hahn, Rohan Shah THE PROBLEM Every AI tool today hits the same wall: they can't reliably access your company's knowledge. Claude Code can't query your Snowflake out-of-the-box. ChatGPT doesn't know your weird custom Salesforce schema. They hallucinate because they lack structured context. The root cause: data infrastructure was built for humans, not AI agents reasoning about business context without tribal knowledge & context. Database access patterns are shifting. SQL won't be how AI systems query data in five years. We're moving to semantic queries, knowledge graphs, self-healing data models. No one has solved this. You'll build the structured context management layer that makes AI context selection reliable in production. This isn't better RAG or fine-tuning. This is inventing new data access patterns and context architectures that power the next generation of AI applications in the fastest changing space around. WHAT YOU'LL BUILD Context Management API Build the context layer AI systems need. Systems that maintain structured context across workflows, self-heal when data changes, and compound knowledge over time. New Data Access Patterns Design semantic query interfaces that replace SQL for AI agents. Build retrieval pipelines that reason about context before querying. Create systems that understand business semantics and go beyond data schemas. Self-Healing Data Models Architect feedback loops that automatically improve data models based on usage. Systems that detect when context breaks and fix it automatically. Knowledge graphs that evolve as the business evolves. Semantic Modeling Infrastructure Users need to be able to improve/expand their data model without data experts. Build the semantic layer that translates business questions & existing reports into precise, verifiable queries. Identity resolution across 50+ enterprise systems. Systems that learn customer language patterns and map them to business outcomes. WHAT WE'RE LOOKING FOR Required • 3+ years building production systems • Experience with retrieval systems, embeddings, vector databases, LLMs or knowledge graphs • Production ML experience: monitoring, versioning, evaluation frameworks • Experience with LLM orchestration (LangChain, LlamaIndex) and multi-agent systems • Familiarity with semantic layers (dbt), data warehouses (Snowflake, BigQuery), enterprise data systems Nice to Have • Enterprise data systems (Snowflake, BigQuery, Salesforce, Segment, Gong) • Multi-agent systems (LangGraph, CrewAI) or workflow orchestration (Airflow, Prefect) • Knowledge graphs, graph databases, semantic layer tools (dbt, Cube) • Real-time data pipelines and streaming architectures TECH STACK Core: Python (primary), TypeScript/JavaScript, SQL LLMs: Anthropic Claude API, OpenAI, in-house frameworks Knowledge Graphs/RAG Data Infrastructure: Snowflake/BigQuery/Redshift, dbt, Kafka/Pulsar, Reverse ETL (Hightouch, Census) Enterprise Integrations: Salesforce, HubSpot, Segment, Gong, Slack, Zendesk, Mixpanel/Amplitude COMPANY CONTEXT Stage: $3.3M pre-seed, proven product-market fit, growing adoption Team: Small senior team from Uber, Lyft, OM1, Capchase. MIT, Princeton, UCSD. You'll be engineer #5-6. Direct collaboration with founders & customers Culture: First-principles debate. Ship multiple times a day . Rapid iteration. In-person in NYC with quarterly off-sites. Compensation: $140K-220K base + meaningful equity. Early-stage upside in proven company. Jai, Saf, & Chirag Co-founders of Deepline

Deepline | In-Person (NYC Preferred) | 3-Month Contract Linear. Vercel. Stripe. They took design as seriously as engineering. Beautiful. Craft is a competitive advantage and they proved it. Deepline is a CLI interface and API that connects 40+ GTM providers. One command. Your database - your interfaces. The interface isn't there yet. CLI doesn’t mean there is no user experience. It means that every interaction point has to be 100x more magical - for both humans and agents. Painful experiences die quickly. Right now our product lives in the terminal - working closely with Claude Code & Codex to solve in minutes what used to take weeks. That's fine for the first 1,000 users. It's not fine for the next 1m. We need someone who makes design decisions while writing production code. You design it, you build it, you ship it. If you've ever opened Figma at midnight because you had an idea for how something should feel and you couldn't sleep until you tried it, we should talk. We're looking for someone who cares about the 2px difference between "good enough" and "just right." What your first 90 days look like Month 1: You ship the marketing site. A full build that makes Deepline look like a company that belongs in the same conversation as Linear and Vercel. You own the visual identity. Typography, color, spacing, motion. Everything starts here. You'll probably redesign the logo while you're at it because you can convince me sans serif is for boomers. Month 2: You refresh the product UI. Dashboards for usage monitoring, team management, provider configuration, cost/usage analytics. You design and build the component library that scales with the product. You're making decisions about information hierarchy that affect how customers understand what Deepline is doing for them at scale. Month 3: You ship the multi-agent onboarding flow. Interactive tutorials, CLI output formatting, error messages that actually help. You create visual content for a product launch. Your work speaks for itself. What you'll own The visual identity. When someone sees Deepline, they should know it immediately. Product UI & UX - for dashboards, workflow builders, provider config, cost/usage analytics Design system. Component library, typography, color, spacing, motion. You build it, you own it. Developer experience layer: CLI output formatting, error messages, onboarding flows Visual content for launches. Product announcements, social assets, changelog, demo videos. Deepline's web presence. Marketing site, documentation, interactive demos. You'll recognize yourself here You've shipped production UI that you designed and built. React/Next.js, Tailwind CSS. Strong opinions about typography, spacing, color, and motion. And you implement those opinions in code, not Figma. You've built with shadcn/ui, Radix, or Framer Motion. You understand component architecture, not just component styling. You care about the details most people don't notice. Loading states. Empty states. Error states. Transitions. Hover interactions. You look at Linear, Vercel, or Stripe and think "I build at that level." Not "I wish I could." You want to define a product's visual language from day one. Not inherit someone else's design system and maintain it. You have a portfolio, a side project, or a Dribbble that you're actually proud of. Show us. Contract terms 3-month contract at market rate Clear conversion criteria discussed upfront. No ambiguity. If we convert: full founding-team comp ($160K-$220k salary depending on experience + 0.50%-1.00% equity) In-person, NYC preferred. Compensation The base pay range for this role is $140,000 – $220,000 per year.