Top Tech Jobs & Startup Jobs

Develop and support secure, scalable full-stack enterprise applications. Build Java and Spring Boot backend services, REST APIs, microservices, and modern frontend components using React or Angular. Collaborate with architects, product owners, QA, DevOps, and global stakeholders in Agile delivery. Participate in testing, code reviews, CI/CD, deployment automation, monitoring, production support, and secure coding practices across cloud-ready systems.

Leads complex, high-value indirect procurement and strategic sourcing initiatives across multiple business lines. Independently manages negotiations, commercial constructs, category strategies, supplier analysis, and value realization. Partners with VP-level stakeholders, develops sourcing pipelines, and supports AI, SaaS, data, and digital transformation transactions. The role also uses analytics, benchmarking, procurement platforms, and risk and governance frameworks to optimize cost, supplier performance, and business outcomes.

Supports reliability, availability, and performance of production applications and platforms. Responsibilities include monitoring, incident response, observability, runbook management, scripting and automation, root-cause follow-up, postmortems, SLO and error-budget adoption, and collaboration with engineering and cloud teams. The role also supports hybrid Azure and Kubernetes environments, operational readiness, AI-assisted investigation, and continuous reduction of alert noise and operational toil.

Develop and maintain automated tests across web, API, and native applications. Apply test methodologies, automation frameworks, CI/CD, test-driven development, Agile practices, and performance testing using JMeter and BlazeMeter. The role requires hands-on test automation experience and proficiency in Java or TypeScript, with Azure DevOps experience preferred or required for cloud and DevOps workflows.

Designs and delivers enterprise-scale Azure lakehouse platforms, data products, ETL/ELT and streaming pipelines using Databricks, Spark, Delta Lake, and related Azure services. Leads and mentors data engineers, establishes engineering standards, drives Agile delivery, and collaborates with technical and business stakeholders. Implements CI/CD, security, governance, monitoring, data quality, lineage, observability, performance tuning, and cost optimization for production data platforms.

Design and implement production-grade AI and machine learning solutions on an enterprise AI platform. Collaborate with product, architecture, business, and platform teams to develop scalable solutions, provide technical guidance, improve platform capabilities, and ensure reliability, observability, quality, and responsible AI compliance. Mentor junior engineers and promote strong software engineering practices, including testing, documentation, and knowledge sharing.

Leads enterprise security architecture reviews for applications, platforms, cloud services, AI solutions, infrastructure, and transformation programs. Performs threat modeling, risk assessments, control evaluations, and security gap analysis. Designs reference architectures and security patterns spanning IAM, networks, devices, applications, data, cloud, SOC, GRC, and AI. Defines target-state architectures, maturity models, roadmaps, access policies, segmentation strategies, and remediation plans while influencing cross-functional stakeholders.

Leads a mid-sized engineering team while designing, building, and modernizing full-stack applications using Java, Spring Boot, microservices, cloud platforms, containers, and CI/CD automation. Collaborates with architects, business stakeholders, and global delivery teams; drives Agile delivery, release readiness, security, quality, observability, change management, and operational stability. The role also requires Japanese conversation skills at JLPT N3 or above.

Designs, develops, and maintains cloud-native Azure data solutions, including data lakes, data marts, pipelines, ETL/ELT processes, and data transformation workflows. Integrates diverse data sources using Azure services, Spark, Python, R, and SQL. Applies Medallion architecture, CI/CD, Agile, DevOps, secure coding, authentication, monitoring, and data quality practices in a containerized environment.

Designs, develops, tests, deploys, and maintains secure, scalable cloud-native full-stack applications using AI-first engineering practices. Translates business outcomes into technical specifications, architecture decisions, and acceptance criteria. Uses AI coding tools responsibly, partners with product and technical teams, supports production incidents, and drives automation and continuous improvement. Requires modern full-stack, API, data, cloud, DevOps, CI/CD, automated testing, and secure software development experience, with preferred exposure to Azure AI Foundry, Semantic Kernel, AI agents, RAG, and LLM applications.