AI Engineer - Private Equity Focus
About TechTorch TechTorch is a high-growth enterprise technology consultancy that partners with the world’s leading private equity-backed businesses. We deliver AI-powered solutions, accelerators, and data-driven transformation initiatives that drive measurable value at speed and scale. Our mission is to redefine enterprise technology consulting for private equity. We combine the agility of a scale-up with the discipline and rigor demanded by the most sophisticated investors and operators. TechTorch was founded by seasoned leaders — including former Bain consultants, CIOs, and tech executives — with deep expertise in technology, transformation, and value creation. We are not a typical startup. We were built to succeed and to deliver results that matter. About the Team TechTorch teams work at the intersection of custom software engineering, modern data platforms, and applied AI . We help private equity-backed companies modernize core systems, build new digital products, and deploy AI solutions that create measurable operational and commercial impact. Our engineers collaborate across backend, frontend, data, and AI disciplines to deliver production-grade, scalable solutions — not demos or slideware.
About the Role
As an AI Software & Data Engineer , you will design and build full-stack software systems , data platforms , and AI-powered MVPs for TechTorch clients. This role is ideal for someone who started in software engineering , developed strong full-stack capabilities , moved into data engineering and analytics , and now applies AI tools and techniques to solve real enterprise problems. You will work end-to-end — from React/Next.js frontends , through backend development in Python and data pipelines , to AI model integration and deployment — owning solutions from concept through production. What You’ll Do Full-Stack Software Engineering Design and build full-stack applications , including: Frontend interfaces using React and Next.js
- Backend services and APIs using
Python and cloud-native patterns
- Develop secure, scalable application logic that integrates with data platforms and enterprise systems
- Implement CI/CD pipelines, testing, and production-readiness standards
- Collaborate closely with product, data, and AI teams to deliver cohesive user experiences
Data Engineering Design, build, and maintain scalable data pipelines and ELT workflows
- Model and manage data in modern data platforms (e.g.,
Snowflake, Redshift, BigQuery, lakehouse architectures )
- Ensure data quality, performance, and lineage across structured and semi-structured data
- Enable analytics, reporting, and downstream AI use cases through well-designed data foundations
Applied AI & Prototyping Build AI prototypes and MVPs end-to-end for clients — from data ingestion to user-facing experience Integrate AI/ML capabilities into software and data workflows (e.g., NLP, document intelligence, classification, anomaly detection)
- Leverage modern AI platforms and services such as
AWS Bedrock, SageMaker, Snowflake Cortex, OpenAI
- Support feature engineering, inference pipelines, and AI-enabled automation
- Ensure AI solutions are observable, explainable, and suitable for enterprise and regulated environments
Who You Are We’re looking for high-caliber professionals who meet the minimum requirements for the role and share our values and mindset. 5+ years of experience across full-stack software engineering and data engineering Strong foundation in custom software development , including: Frontend: React, Next.js Backend: Python , strong API and service design Solid hands-on experience with data engineering : pipelines, modeling, warehouses, ELT/ETL Practical experience building and deploying AI-powered prototypes or MVPs , not just experimentation Proficient in Python , SQL, and modern cloud-native development practices
- Experience with
cloud platforms (AWS preferred; Azure or GCP acceptable)
- Comfortable operating across software, data, and AI — able to wear multiple hats
- Strong problem-solving skills and ability to translate business needs into techni
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