Top Remote Entry Level Software Engineer Jobs in Boston, MA

As an Outcome Engineer, you will architect multi-agent systems, implement automated governance, and build evaluation frameworks to enhance AI-powered workflows.

The Quantitative Developer will assist with client onboarding, support, implement and maintain new functionality for portfolio compliance, and improve team documentation.

Develop and improve Scala, Bazel, and CI foundations used by engineering teams. Build shared libraries, frameworks, automation, and developer tools; improve build reliability and feedback loops; debug workflow failures; and partner with product engineers on platform adoption. The role also applies AI-assisted engineering tools and agentic workflows to accelerate development while maintaining safety, quality, and human oversight.

Build and operate core platform systems for users, workspaces, permissions, APIs, authentication, and resource management. Deliver full-stack features with a backend focus, including admin and settings interfaces. Scope work within large existing systems, plan migrations, manage safe rollouts, debug production issues, and collaborate across product and engineering teams. Candidates need strong Python and backend development expertise, software and system design knowledge, testing and security fundamentals, and the ability to navigate ambiguity.

Design, develop, secure, modernize, and support scalable omnichannel APIs for customer-facing web, mobile, contact center, partner, and enterprise applications. Improve API security, resiliency, performance, observability, testing, and reliability. Collaborate with architecture, security, cloud, product, operations, and engineering teams; lead technical delivery, mentor engineers, develop reusable patterns, and provide Tier 3 production support. Apply AI-assisted engineering practices and contribute to API lifecycle management and continuous improvement.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Build and ship React and TypeScript interfaces for a Chrome extension and web apps, partnering on UI/UX, accessibility, performance, data models, APIs, and AI-generated scaffold quality. Contribute to Node.js and MongoDB systems, expand compatibility across educational platforms and documents, and support privacy, security, reliability, and product decisions on a small startup team.

Build production-grade automation workflows, integrations, custom nodes, and reusable patterns for strategic enterprise deployments. Embed with customers during focused on-site engagements, translate ambiguous business problems into practical technical solutions, and collaborate with Deployment Strategists, Product, and Engineering. Capture customer feedback for product improvements, create internal playbooks, and deliver scalable solutions that customers can operate independently. The role requires frequent travel, strong engineering and integration skills, customer-facing confidence, and sound technical judgment.

Leads and coaches a software engineering team, supports career development, participates in hiring, removes delivery roadblocks, and shapes technical direction. The manager ensures reliable, high-performing systems while driving daily adoption of agentic AI tools and collaborating with Product and Business Technology stakeholders. The role requires a strong full-stack engineering background, architectural expertise, experience delivering quality software, and demonstrated success leading AI adoption.

Hands-on fellowship for university students and recent graduates interested in AI, backend engineering, cloud infrastructure, and software delivery. Fellows may research technology trends, build internal tools and automation workflows, explore LLM-powered agents, prototype backend or cloud solutions, and prepare technical documentation and client-readiness materials. The role emphasizes ownership, reliability, clear technical communication, and practical project experience.