Top Tech Jobs & Startup Jobs

Lead full‑stack development using Core Java 11 and Spring Boot modules, build reusable front- and back-end components, design web architecture with HTML5/CSS/JavaScript/React, collaborate in Agile scrum teams, and ensure secure, scalable, high-performance solutions while articulating architectural decisions.

Lead cross-functional engineering teams to plan and deliver software features through the agile lifecycle. Drive technical planning, architecture, risk mitigation, backlog prioritization, cross-team integration, reporting, and continuous improvement while mentoring engineers and coordinating with product and design stakeholders.

Lead end-to-end architecture for an Azure-based digital banking platform: design cloud platform, integration, security, resiliency, and DevSecOps. Own solution, backend/microservices, BFF, reference architectures, ADRs, and production readiness while guiding engineering, vendors, and compliance (PCI-DSS).

Drive day-to-day delivery of search and catalog discovery features for a B2B automotive parts platform. Own and groom the sprint backlog, write sprint-ready user stories and BDD acceptance criteria, coordinate with API/frontend engineers, QA, and stakeholders, and ensure release readiness, validation, and post-launch monitoring for parts search, vehicle fitment, PLP/PDP, pricing, and availability workflows.

Design, build, evaluate, and deploy predictive ML models across regression, classification, NLP, computer vision, and time-series problems. Perform data cleaning, feature engineering, EDA, model selection, tuning, explanation (SHAP, feature importance), and collaborate with engineers and stakeholders to operationalize and monitor models in production.

Design, build, and maintain scalable backend services and APIs using Java and Spring Boot. Implement event-driven architectures with Kafka, manage PostgreSQL/Redis data, ensure performance and reliability, troubleshoot production issues, participate in code reviews, and collaborate across teams for deployments and monitoring.

Lead design and delivery of large-scale agentic AI platforms: define architecture patterns, build multi-agent workflows and RAG systems, optimize performance, establish MLOps/CI/CD practices, run POCs with stakeholders, mentor teams, and maintain technical documentation.