AI Software Data Engineer
TechTorch
full-time
Posted on:
Location Type: Remote
Location: United States
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Tech Stack
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.
- 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.
- 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.
- 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.
- 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.
Requirements
- 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
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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
full-stack software engineeringdata engineeringReactNext.jsPythonAPI designdata pipelinesELTSQLAI/ML integration
Soft Skills
problem-solvingclient-facing experiencecollaborationcommunicationadaptability