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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