Pre-screened and vetted in the Greater Boston.
Mid-Level Backend Software Engineer specializing in Java, Spring Boot, and Cloud DevOps
Intern Full-Stack AI Engineer specializing in LLM automation and RAG systems
Mid-level Software Engineer specializing in full-stack systems and cloud-native platforms
Mid-level Software Engineer specializing in backend and cloud-native FinTech systems
Entry-Level Software Engineer specializing in full-stack web development and healthcare IT
Junior Full-Stack Software Engineer specializing in AI-powered developer tools
Mid-Level Software Engineer specializing in Salesforce and AI automation
Lead Software Engineer specializing in payroll and workforce data platforms
Junior Software Engineer specializing in AI and full-stack development
Mid-level AI Software Engineer specializing in FinTech and LLM systems
Mid-level Full-Stack Software Engineer specializing in FinTech microservices
Junior Backend and AI Engineer specializing in regulated healthcare and legal systems
Mid-level Full-Stack Software Engineer specializing in platform and legacy modernization
Mid-level QA Analyst and Software Engineer specializing in game and web application testing
Intern Full-Stack Software Engineer specializing in web apps and distributed systems
“Built an itinerary-planning startup MVP (LessGO) using React/TypeScript and a Node/Express backend integrating Google Maps and Gemini AI. Notably optimized Gemini latency from ~40 seconds to ~3 seconds through frontend caching, debugging, and model selection, and has TA experience supporting others with deployments and database connectivity.”
Junior Software Engineer specializing in full-stack web and cloud systems
“Co-op engineer at EnFi who built and maintained a multi-tenant prompt library and LLM workflow tooling used by internal teams and external enterprise clients. Led TypeScript/React package design and standardized a typed workflow abstraction across disparate implementations (React, Go, JSON), improving reliability and developer adoption. Delivered measurable performance gains (~25% latency reduction) and owned end-to-end execution including docs, demos, debugging, and deployment.”
Mid-level DevOps/Cloud Engineer specializing in AWS infrastructure automation
“Frontend engineer with experience building a large-scale React + TypeScript administrative dashboard for an e-commerce platform, using Redux Toolkit plus TanStack Query to separate UI and server state. Emphasizes quality at scale through CI/CD automation, Jest/integration testing, and performance techniques like code splitting and caching, with experience coordinating integration across multiple teams.”
Mid-level Software Engineer specializing in cloud-native data pipelines and ML platforms
“Backend engineer who has owned end-to-end delivery of Python/FastAPI microservices for real-time data processing and alerting, including performance tuning (Postgres optimization, caching, async processing). Strong DevOps/GitOps background: Docker + Kubernetes deployments with GitHub Actions CI/CD and ArgoCD-driven GitOps, plus experience supporting phased on-prem to AWS migrations and building Kafka-based streaming pipelines.”
Junior Software Engineer specializing in distributed systems, DevOps, and observability
“Built and launched a verified listings system for Burrow (student subleasing) after interviewing ~50 students about scam/fake listing concerns; chose a lightweight .edu-based verification approach to ship fast and then iterated with badges and clearer details, reducing churn from 15% to 7%. Also ran an LLM A/B test for auto-generating listing descriptions and improved trust/accuracy by updating prompts to prevent hallucinated details.”
Junior Full-Stack Software Engineer specializing in TypeScript/React and microservices
“Software engineer who built and owned an internal workflow automation + analytics platform end-to-end (TypeScript/React/Node) with a microservices, RabbitMQ-based async architecture. Drove adoption by shipping iterative prototypes and prioritizing reliability/performance (Redis caching, query optimization), delivering ~30–35% latency improvements and ~30–40% reduction in manual operational work.”