AI Product Engineer
Mindtickle
Job Overview
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Job Description
Role Overview
Mindtickle is transitioning to an AI-first operational model. The AI Product Engineer will architect and build the company’s central intelligence engine by creating automated intelligence systems that retrieve insights, trigger workflows, and synthesize strategic information across the business.
Role Profile
This high-impact, hands-on engineering role requires expertise in three key areas:
- Software Engineering (50%): Building scalable middleware, API integrations, and production-grade applications.
- AI Engineering (30%): Implementing agentic workflows, RAG architectures, and LLMs for processing data at scale.
- Data Analytics (20%): Leveraging SQL and B2B SaaS metrics ensuring accuracy and governance.
Key Responsibilities
Enterprise Brain Development: Develop a unified intelligence layer that ingests data from various sources and transforms it into actionable outputs. Build robust integrations to push AI-generated insights into workflow tools like Salesforce.
AI Logic & Agent Implementation: Architect agentic workflows that allow LLMs to perform tasks, implement advanced RAG to ground outputs in company data, and ensure guardrails to prevent model hallucinations.
Data Engineering & Governance: Collaborate with Analytics Engineers to support real-time AI applications and maintain security and privacy standards across departments.
Qualifications
Minimum Qualifications: Bachelor’s degree in Computer Science or equivalent, 3+ years of Python development experience, strong API development skills (FastAPI/Django), expertise in LLM integration and orchestration, and solid SQL skills with familiarity in cloud data warehouses like Snowflake or BigQuery.
Preferred Qualifications: Experience with major B2B tool APIs (Salesforce, HubSpot, Zendesk, Jira, Marketo), advanced workflow automation tools (Airflow, Zapier/Make), and B2B domain expertise in Sales, Product, and Customer Success.
Competencies
The Builder Mindset: Ability to take strategic requirements and independently architect solutions. Systemic Thinking: Understand downstream effects of product data schema changes. Adaptability: Switch contexts rapidly between technical tasks and strategic problem-solving.
Key skills/competency
- AI
- Product Engineering
- Software Engineering
- API Integration
- LLM
- Data Analytics
- Middleware
- Agentic Workflows
- SQL
- Workflow Automation
How to Get Hired at Mindtickle
- Customize your resume: Emphasize Python and API integration expertise.
- Highlight AI projects: Detail experience with LLMs and agentic workflows.
- Showcase data skills: Include SQL and data engineering achievements.
- Prepare for technical interviews: Review system design and middleware development.
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