techtorch - AI Software Data Engineer US
Requirements
• 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 technical solutions • Consulting or client-facing experience is a strong plus • Snowflake (including Cortex AI), dbt, Airflow, Spark • AWS services: Lambda, Step Functions, Bedrock, SageMaker • Exposure to MLOps, model lifecycle management, or AI governance • Experience in regulated or data-sensitive environments • Client First — We focus relentlessly on delivering outcomes that create value for our clients • We, Not Me — We win together. Collaboration drives transformation at scale • Get Stuff Done — We execute with speed and precision — because in PE, time matters • AI First — We embed AI at the core, enabling scalable, high-leverage solutions • Own It — We take accountability for results, delivering on what we promise • Agile Mindset — We adapt quickly and proactively seek better ways to move forward
Responsibilities
• 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
Benefits
• A role at the intersection of full-stack software, data engineering, and applied AI • Ownership of end-to-end AI prototypes and production systems • High-impact projects with private equity firms and their portfolio companies • A global, senior team focused on delivery excellence • Flexible, remote-first working environment with high autonomy
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