---
title: "AI Product Engineer"
company: "Mindtickle"
company_url: "https://www.remjobs.works/companies/mindtickle"
url: "https://www.remjobs.works/job/mindtickle-ai-product-engineer-517adb29-75e4-4db9-86b1-83cb0d0cac85"
apply_url: "https://jobs.lever.co/mindtickle/864ac315-d7c5-4cd5-ab44-0e33d08f48f1"
workplace: hybrid
location: "Pune, Maharashtra"
employment_type: full-time
seniority: mid
role: ai-machine-learning
region: india
skills: ["airflow", "django", "hubspot", "jira", "llm", "python", "salesforce", "snowflake", "sql"]
date_posted: 2026-09-09T08:59:48.738Z
first_seen_by_remjobs: 2026-09-09T09:29:13.328Z
---

# AI Product Engineer

**Mindtickle** · Pune, Maharashtra

Apply: https://jobs.lever.co/mindtickle/864ac315-d7c5-4cd5-ab44-0e33d08f48f1

## About Mindtickle

The Mindtickle Revenue Enablement Platform is a solution for your entire sales team to elevate team performance, achieve more sales quotas, and drive revenue

## About the role

##### Role Overview

We are transitioning our organization to an AI-first operational model. We are seeking an **AI Product Engineer** to architect and build the company’s central intelligence engine.

In this role, you will be the primary builder of **automated intelligence systems**—tools that not only retrieve insights but actively trigger workflows, and synthesize strategic intel across our entire business landscape.

##### Role Profile

This is a high-impact, hands-on engineering role requiring a convergence of three distinct skill sets:

1. Software Engineering (50%): Building scalable middleware, API integrations, and production-grade applications that connect our data stack to business tools (CRM, Marketing Automation, Support/Ticketing).

2. AI Engineering (30%): Implementing Agentic workflows, RAG architectures, and LLMs to process unstructured data at scale.

3. Data Analytics (20%): Leveraging SQL and B2B SaaS metrics to ensure all automation is grounded in accurate, governed data.

##### Key Responsibilities

**1. Building the "Enterprise Brain" (Architecture & Integration)**

- Develop a unified intelligence layer that ingests signals from disparate sources (Product Telemetry, CRM, Call Transcripts, Marketing inputs) and processes them into actionable outputs.

- Build robust integrations/webhooks to push AI-generated insights directly into workflow tools (e.g., pushing "Churn Risk" alerts into Salesforce

**2. AI Logic & Agent Implementation**

- Architect "Agentic" workflows where LLMs are granted permission to perform tasks

- Implement advanced RAG to ground AI outputs in company documentation, historical data, and strategic context.

- Ensure rigorous evaluation and guardrails for non-deterministic models to prevent "hallucinations" in critical business workflows.

**3. Data Engineering & Governance**

- Collaborate with Analytics Engineers to ensure the underlying data pipelines support real-time or near-real-time AI applications.

- Maintain security and privacy standards, ensuring that AI agents respect data access permissions across different departments.

##### Qualifications

**Minimum Qualifications:**

- Education: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

- Software Engineering: 3+ years of experience in Python development, with strong proficiency in API development (FastAPI/Django) and building integrations between SaaS platforms.

- AI/ML Application: Proven experience building applications using LLM APIs and orchestration frameworks, Experience with "Agent" concepts.

- Data Proficiency: Strong SQL skills and familiarity with cloud data warehouses (Snowflake/BigQuery).

**Preferred Qualifications:**

- Business Systems Knowledge: Experience working with APIs for major B2B tools (Salesforce, HubSpot, Zendesk, Jira, Marketo).

- Workflow Automation: Experience with tools like Airflow, Zapier/Make (advanced usage), or custom workflow engines.

- B2B Domain Expertise: Understanding of the interplay between Sales, Product, and Customer Success.

##### Competencies

- The "Builder" Mindset: You are comfortable taking a high-level strategic requirement from leadership (e.g., "We need to automate lead qualification") and independently architecting and coding the solution.

- Systemic Thinking: You understand how a change in product data schema impacts the downstream marketing automation flow.

- Adaptability: You can switch contexts rapidly—from debugging a SQL query for Strategy to refining a prompt for Customer Support automation.

---

Source: Mindtickle's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/mindtickle-ai-product-engineer-517adb29-75e4-4db9-86b1-83cb0d0cac85