Top Tech Jobs & Startup Jobs in Boston, MA

The Customer Success Manager will manage relationships with ~100 customers, driving feature adoption, retention, and revenue growth while ensuring they achieve business objectives using Paperless Parts' software.

Lead end-to-end delivery of customer integration projects: design, develop, test, deploy, and support integrations between Paperless Parts and customer systems (ERP, CRM, MES). Drive discovery, gather requirements, troubleshoot production issues, manage multiple engagements, and expand reusable integration frameworks. Mentor teammates and help scale the Services Engineering organization.

As a Technical Implementation Specialist, you will lead customer onboarding projects by building their quoting workflows, leveraging the Paperless Parts platform and P3L coding language while providing ongoing support and maintaining relationships with customers.

Provide technical support and product expertise to customers, specializing in the P3L pricing language and third-party integrations. Troubleshoot and configure customer requests, handle high-volume support cases, deliver training, surface product feedback, and partner with Customer Success to drive adoption and expansion.

Lead enterprise implementations for a SaaS startup, guiding customers through project management, system integrations, and process transformations while ensuring value and effectiveness in execution.

The Senior Technical Project Manager leads enterprise implementations, driving project delivery, managing resources, and achieving business outcomes while collaborating with customers and internal teams.

The Business Development Representative will engage in outbound sales, manage leads using Salesforce, and support marketing efforts while fostering DEI initiatives.

Entry-level Platform Engineer responsible for building and maintaining scalable, secure AWS-based infrastructure using Terraform, improving CI/CD pipelines (Jenkins), creating Datadog monitoring dashboards, writing automation scripts (Python/Bash), working with Docker, and participating in sprint and on-call duties while learning from senior engineers.

Build and maintain full-stack features across Python backends and React frontends, design secure APIs, apply AI tools across the SDLC, mentor engineers, improve testing/observability, and collaborate with product and design to deliver scalable, production-ready systems.

Lead a small ML engineering pod to turn research into production: design and operationalize training pipelines and low-latency inference services for computer vision, document intelligence, and predictive models. Drive R&D execution, benchmarking, prototyping, migrations from frontier models to fine-tuned/open-source solutions, and mentor early-career engineers while aligning research with product timelines.