AI Product Engineer

Mindtickle; Maharashtra; On-site; INR 2,500,000 - 3,800,000; Full time

Job summary

Mindtickle in Maharashtra, India, seeks an AI Product Engineer to architect and build the company’s central intelligence engine. You will craft automated intelligence systems that not only retrieve insights but also trigger workflows and synthesize strategic intel across the business landscape.

The role blends software, AI, and data analytics: develop scalable middleware and integrations with CRM/Marketing tools, implement LLM-based workflows, and ensure governance for real-time AI applications.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years of Python development with API development and building integrations between SaaS platforms.
• Proven experience building applications using LLM APIs and orchestration frameworks.
• Strong SQL skills and familiarity with cloud data warehouses (Snowflake/BigQuery).
• Experience with APIs for major B2B tools (Salesforce, HubSpot, Zendesk, Jira, Marketo).
• Experience with workflow automation tools like Airflow, Zapier/Make, or custom engines.

Responsibilities

• Build the Enterprise Brain architecture and integration layer.
• Develop unified intelligence layer that ingests signals from disparate sources and outputs actionable outputs.
• Build robust integrations/webhooks to push AI-generated insights into workflow tools (e.g., churn risk alerts into Salesforce).
• Design AI logic and Agent implementations for automated workflows.
• Architect Agentic workflows with LLMs performing tasks.
• Implement advanced RAG to ground AI outputs in company docs and data.
• Ensure strict evaluation and guardrails for non-deterministic models.
• Collaborate with Analytics Engineers to support real-time AI applications.
• Maintain security and privacy standards across departments.

Skills

Python development

API development

LLM APIs

SQL

Education

Bachelor’s degree in Computer Science or Engineering

Tools

FastAPI

Django

Snowflake

BigQuery

Airflow

Zapier/Make

Job description

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:

• 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).

• AI Engineering (30%): Implementing Agentic workflows, RAG architectures, and LLMs to process unstructured data at scale.
• Data Analytics (20%): Leveraging SQL and B2B SaaS metrics to ensure all automation is grounded in accurate, governed data.

Key Responsibilities

Qualifications

• 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
• 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.
• 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.

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.