You design, build, and operate the AI-powered technical systems that power our pipeline from signal detection through deal acceleration. This isn't a marketing role with a technical veneer. You write code, deploy AI agents, build data pipelines, and create the automation infrastructure that lets a lean GTM team punch way above its weight.

A sales rep who walks into every meeting with AI-generated account research, real-time competitive intel, and a prospect-specific value narrative that's your system at work. You make that possible.

Pipeline Intelligence Infrastructure The candidate will have responsibilities across the following functions :

- Data foundation for our two-path pipeline model: founder/partner-sourced deals and marketing-sourced leads running the full funnel.
- Enrichment workflows, ICP scoring models, and signal-based triggers that surface the right accounts at the right time.
- Integration of Clay, AI agents, and third-party data sources into a unified account intelligence layer.

AI-Native Outbound Systems

- AI-powered outbound engines targeting CISOs, IAM leaders, and identity security buyers across enterprise and state/federal accounts.
- Personalised campaign systems that generate, test, and optimise messaging variants at scale programmatically, not manually.
- Automated A/B testing infrastructure across channels, messaging, and timing.

CRM And RevOps Automation

- Automated lead routing, opportunity management, forecasting inputs, and handoff workflows.
- Connected GTM stack: CRM, enrichment, sequencing, and analytics in one coherent system.
- Data quality enforcement: clean, current, and actionable pipeline data at all times.

Sales Enablement Tooling





- Automated competitive intelligence updates and AI-generated account research briefs.
- Dynamic battle cards and prospect-specific leave-behinds.
- Internal tools that accelerate every stage of the sales cycle.

Measurement And Feedback Loops

- Dashboards tracking pipeline velocity, conversion rates, campaign attribution, and system health.
- Feedback loops so the GTM machine gets smarter with every cycle.
- Data pipelines connecting marketing, sales, and product signals.

Requirements

- 3-5 years as a full-stack or application engineer, with strong front-end skills (React/Next.js preferred).
- Experience building customer-facing tools, interactive experiences, or PLG features - not just internal dashboards.
- Comfortable with data: APIs, ETL pipelines, database design, and integrating multiple data sources.
- Experience with or solid interest in Clay, Segment, or similar GTM data platforms.
- You build fast. You ship MVPs in days, iterate based on data, and don't wait for perfect requirements.
- You use AI coding tools (Cursor, Copilot, Claude) as a daily multiplier.
- Interest in cybersecurity and identity: You don't need to be an expert, but you're curious about the space.

Nice To Have

- Experience building PLG tools at a B2B SaaS company.
- Familiarity with Salesforce/Pardot data models.
- Experience with AI/ML for scoring, classification, or recommendation systems.
- Background in developer tools, security tools, or enterprise infrastructure.
- Experience with AI/ML for scoring, classification, or recommendation systems.
- Background building PLG tools, internal tools, or developer platforms at a B2B SaaS company.
- Prior work at a Series A-C startup where you wore multiple hats.

This job was posted by Rajneesh Kumar from Oleria.

📌 AI Applications Engineer (Bengaluru)
🏢 Oleria
📍 Bengaluru