Top Tech Jobs & Startup Jobs

Design and build end-to-end AI systems: partner with business stakeholders, develop data pipelines and retrieval layers, create and evaluate LLM-based applications and ML models, ensure data quality and observability, and ship production-ready AI solutions that deliver measurable business impact.

Build and operate model training, fine-tuning, and inference platforms for enterprise AI. Design deployment pipelines for LLMs and ML models, optimize inference across accelerators, enable distributed training and autoscaling, and implement monitoring, alerting, rollback, and versioning to ensure reliable, cost-efficient production AI in a regulated financial environment.

Operate and improve KKR's AI platform infrastructure: own CI/CD, Terraform, cloud networking, secrets, observability, incident response, and cost optimization for AI and data services. Partner with AI Engineering/Infrastructure to automate developer workflows and ensure reliable, secure, scalable GPU-enabled workloads.

The Finance Associate manages financial oversight of APAC SPVs, ensuring accurate reporting and compliance, while coordinating with administrators for monthly closes and budget reviews.

The Salesforce Developer will deliver Salesforce solutions, manage projects independently, optimize performance, and provide technical leadership within KKR's tech team.

Drive distribution and AUM growth across private wealth platforms in Hong Kong and Taiwan by building distributor relationships, delivering product education, prospecting, coordinating with global GWS, supporting go-to-market and after-sales, maintaining CRM and sales reporting, and assisting cross-functional product and business initiatives.

Administer the firm's compensation programs and data, support year-end planning and benchmarking, perform complex Excel modeling and analyses, respond to ad-hoc reporting requests, partner on HRIS/reporting improvements, and conduct ongoing data audits to ensure accuracy.

Design, build, and maintain scalable batch and real-time data pipelines and ingestion frameworks. Develop modular, tested ETL/ELT transformations with dbt, ensure data quality, modeling, governance, lineage, and security. Monitor, troubleshoot, and optimize pipelines while collaborating with analytics, data science, and product teams to deliver production-ready data for reporting and advanced analytics.

Design, build, and maintain scalable batch and real-time data pipelines and ingestion frameworks. Develop modular ELT/ETL transformations with dbt, ensure data quality, model data for analytics, monitor pipelines, troubleshoot performance issues, and implement governance, lineage, and documentation to enable analytics and data science teams.