Data Engineer - AI-First Staffing Platform

Job Description

Job Description

Location : Boston (Hybrid)

Reports to : Head of Engineering

Type : Full-time

About AdeptID

AdeptID is building an AI-first staffing company. Over five years, we've built a talent-matching engine that powers 10 million job recommendations every month for major HR technology platforms. We're now using that technology to support an end-to-end staffing firm for the healthcare sector – focused on solving healthcare talent shortages with AI. We're backed by top investors and poised to 10x our footprint by 2027.

Role Overview

We're seeking a mid-level or senior Data Engineer to build and evolve the data backbone of AdeptID's AI-first staffing platform. Our systems process millions of talent and job records monthly, ensuring that data is reliable, high-quality, and secure.

You'll design production data pipelines, automate manual workflows, and work closely with software and data science teams to make machine-learning models production-ready. This hands-on role combines immediate impact with long-term growth : you'll deepen your expertise in modern data infrastructure while gaining experience in MLOps, AI data pipelines, and infrastructure-as-code on AWS – all in a supportive, learning-oriented environment that values curiosity and shared success.

If you're motivated by solving data challenges at scale and excited to build and learn about high-performing AI systems, you'll thrive here.

Responsibilities

• Design, build, and maintain scalable ETL and data pipelines in Python on AWS
• Automate manual data workflows to improve repeatability and speed
• Monitor and optimize pipelines for reliability, latency, and data quality
• Create code, systems, and policies for handling sensitive / PII information at scale
• Develop and maintain data environments with infrastructure-as-code on AWS
• Contribute to observability and performance monitoring – defining metrics and dashboards that highlight system health
• Partner with data scientists and ML engineers to develop data flows powering model training, evaluation, and inference
• Collaborate in reviews and design discussions to help set standards for data-engineering best practices
• Document schemas, transformations, and data lineage for transparency and maintainability

Qualifications

Next Steps

Well-qualified candidates will be invited to submit short responses to a set of screening questions and meet with a member of the hiring team.