Top Entry Level Jobs in Boston, MA

The AI-Native Quality Engineer will establish software validation capabilities using AI and automation. Responsibilities include automation, specification clarity, and exploring AI in quality engineering, requiring strong programming and API experience.

The Cloud Technical Support Engineer - Co-op aids enterprise customers with application integration, supports deployment, engages with engineers on service enhancement, and assists in diagnosing issues related to Wasabi's cloud storage.

As a Specialist in Customer Experience, you'll provide exceptional service, upsell features, and streamline interactions for healthcare providers, ensuring a positive and effective use of Zocdoc's platform.

The Crypto Trader role involves executing trades, analyzing market data, managing risks, and developing trading skills in a supportive environment with full training provided.

The Customer Support Specialist will troubleshoot customer issues, manage support requests, educate clients, and improve internal processes while collaborating with various teams.

As a Loan Processing Representative, you will process loan applications, handle customer inquiries, and ensure compliance with quality standards, primarily through phone communication.

The Account Operations Support Associate assists campaigns and organizations with support requests, processes tickets, reconciles financial reports, and manages account setups while ensuring organizational objectives are met.

Drive new customer acquisition and revenue growth as part of the Outbound Sales Development team. Collaborate with cross-functional teams to build a strong sales pipeline and understand customer needs in the ASR space.

The Encompass Admin oversees configuration and support for the Loan Origination System, addressing issues, managing user roles, and documenting requirements.

Protect CrowdStrike intellectual property by detecting and investigating eCommerce fraud. Build and maintain Snowflake data pipelines and SQL queries, develop rules-based risk engines, leverage Python and AI/LLM tools for detection, triage incidents, communicate findings across stakeholders, and refine automated workflows to reduce fraud and onboarding vulnerabilities.