Top Tech Jobs & Startup Jobs

Build and maintain automated browser and API tests using C#, Selenium WebDriver, and NUnit. Plan pre-merge verification, expand test coverage, manage parallel test data, diagnose failures, and improve CI/CD pipelines. Collaborate with engineering, product, and quality teams to identify coverage gaps, improve application testability, review test code, and promote quality engineering practices.

Build and deploy production-grade Generative AI applications using Python, LLMs, RAG pipelines, semantic search, vector databases, and cloud platforms. Develop scalable REST APIs, integrate commercial and open-source models, optimize prompts and AI evaluations, and improve system reliability, latency, scalability, and cost. Collaborate with cross-functional engineering teams while following software development, testing, code review, and CI/CD best practices.

Tests insurance and reinsurance risk-modeling software in an agile environment. Responsibilities include analyzing requirements, creating and executing test plans, automating tests, debugging issues, maintaining acceptance and regression repositories, documenting defects, tracking results, communicating status, improving QA processes, and supporting new-hire training. The role collaborates with product, development, client services, and global teams.

Owns post-sale commercial relationships for the FAST platform, serving as the executive customer contact and driving renewals, expansion, adoption, and revenue growth. Responsibilities include account planning, executive governance, customer launches, value realization, forecasting, commercial negotiations, cross-functional coordination, barrier resolution, and market support. The role requires strong insurance industry knowledge, executive presence, technology transformation skills, and 10+ years of customer-facing or consulting experience.

Performs catastrophe risk and loss analyses supporting catastrophe bonds and insurance-linked securities transactions. Produces risk reports, supports investor presentations, reviews transaction documents, maintains analytical databases and tools, provides client troubleshooting and event support, and leads training sessions. The role combines financial analytics, catastrophe modeling, reinsurance expertise, and client-facing service.

Build and operate AWS and Kubernetes production platforms, develop Terraform and OpenTofu infrastructure patterns, automate with Ansible, and improve CI/CD, observability, security, governance, and developer self-service. The role investigates complex platform issues, supports AI technology adoption, strengthens operational reliability, mentors engineers, and influences engineering standards across teams.

Analyze catastrophic insurance claims data and validate financial and uncertainty models using statistical methods, simulations, and code in R or C++. Document methodologies, assess model accuracy, create visualizations and presentations, and communicate technical findings to internal and client-facing teams. The role focuses on catastrophe risk, probability, insurance concepts, and quantitative modeling.

Owns and improves enterprise Linux infrastructure across on-premises and cloud environments. Responsibilities include automating deployments with Ansible, building reliability tools, designing CI/CD pipelines, writing scripts and code, troubleshooting complex production issues, supporting HPC compute and storage environments, and participating in maintenance and incident response.

Sources strategic and hard-to-fill talent across APAC while managing recruiting operations. Responsibilities include building talent pipelines, conducting market research, coordinating interviews, maintaining Oracle Recruiting data quality, governing processes, supporting recruiting technology and AI workflow adoption, producing reports, and partnering with regional recruiters, TA leads, hiring managers, and global TA enablement teams.

Design and deploy production-grade generative AI and agentic AI applications. Build Python full-stack systems, LLM-powered solutions, RAG workflows, AI agents, APIs, microservices, and database integrations. Deploy cloud-native applications on AWS while establishing evaluation, monitoring, guardrails, governance, security, and performance practices. Collaborate with cross-functional teams to deliver reliable AI products and maintain high standards for code quality and documentation.