Jobs at Livecareer

Design, architect, and deliver scalable full-stack software from concept through deployment. Collaborate with Product Owners to shape technical solutions, solve ambiguous problems, integrate AI coding tools and LLM-powered features, and maintain quality through testing, observability, refactoring, code reviews, and deployments. Build production systems using TypeScript, Node.js, React, Next.js, SQL, and PostgreSQL.

Analyze large payment datasets to identify patterns in acceptance, chargebacks, and fraud. Monitor and forecast payment metrics, build financial and statistical models to assess KPI drivers, recommend processor allocation and anti-fraud improvements, and collaborate with development to implement platform changes and reporting tools to optimize e-commerce payment performance.

Design, implement, and maintain large-scale browser automation scripts and monitoring systems. Build CI/testing strategies, debug intermittent failures and complex DOM patterns, collaborate cross-functionally, mentor junior engineers, and contribute across the software lifecycle.

Own the full lifecycle of B2B sourcing products, including roadmap strategy, customer discovery, platform integrations, onboarding optimization, experimentation, and go-to-market execution. Lead cross-functional agile squads, define requirements and priorities, improve adoption and retention, measure product performance, and advise leadership. The role requires strong analytical, stakeholder management, customer insight, and execution skills across complex HR technology ecosystems.

Develop and maintain scalable web-based products and distributed microservices using .NET technologies. Responsibilities include translating requirements into applications, writing clean and reliable code, designing for high load and scalability, troubleshooting bottlenecks, collaborating with business and engineering teams, and maintaining code quality and automation.

Lead the design, development, optimization, and maintenance of scalable enterprise applications using Java and Spring Boot. Build high-performance REST, gRPC, and GraphQL APIs; ensure production reliability, security, and scalability; participate in architecture planning and code reviews; collaborate with product, DevOps, and QA teams; mentor junior engineers; and troubleshoot production issues through root cause analysis and long-term remediation.

Design, develop, and maintain scalable enterprise applications using Java and Spring Boot. Build high-performance REST, gRPC, and GraphQL APIs; implement event-driven microservices; and leverage AWS, containers, Kubernetes, Terraform, and CloudFormation. Troubleshoot production issues, optimize performance, support reliable deployments, participate in architecture and code reviews, and mentor junior engineers while collaborating with product, DevOps, and QA teams.

Design, build, and maintain scalable Python applications and distributed microservices running on Kubernetes. Develop web scraping and browser automation solutions using Playwright and Chromium, optimize performance, implement messaging and caching, troubleshoot complex issues, and ensure reliability, security, and data privacy. Collaborate with product and cross-functional teams, participate in testing and code reviews, document architecture, and apply DevOps and CI/CD practices.

Principal Engineer responsible for designing scalable, secure, distributed software architectures and guiding development teams. The role includes developing web applications with Microsoft technologies, evaluating tools, conducting code reviews, ensuring architectural compliance, troubleshooting complex issues, and delivering production-quality code and tests. The engineer will collaborate with architects and senior leaders while defining technical standards, workflows, system integrations, and solutions for high-transactional products.

Develop predictive models, NLP and machine learning systems using large user datasets to improve search, matching, recommendations, and other digital products. Build scalable data products with Engineering and Product teams, applying statistical analysis, vector search, LLM/RAG techniques, embeddings, classifiers, and deep learning. Collaborate across teams to research new methods and deliver production-ready software.

Develop predictive models, NLP and machine learning systems using large user datasets to improve products and create new data products. Responsibilities include statistical analysis, scalable data system development, prompt engineering, large language model benchmarking, and agentic workflow experimentation. The role collaborates with Engineering, Product, BI, Legal, and Management teams and may involve production model deployment and backend development.

Administer and support Microsoft SQL Server databases across Azure and on-premise environments. Responsibilities include database architecture, performance tuning, migrations, maintenance, backups, recovery, security, integrity, high availability, disaster recovery, capacity planning, monitoring, and automation. The role also troubleshoots resource contention, blocking, deadlocks, and integrity issues while participating in incident, change, and problem management and coordinating technical solutions with stakeholders and architects.

Lead strategy and execution for the digital storefront to optimize path-to-purchase and lifetime value. Coordinate cross-functional squads, run advanced A/B experimentation, define metrics and event tracking, prioritize roadmap based on user insights, and collaborate with engineering on technical tradeoffs to drive conversion and revenue.

Support the SEO Leader executing technical and on-page SEO tactics for international sites. Perform audits, competitor analysis, implement optimizations, manage SEO tasks end-to-end, monitor performance, collaborate with Product/Design/Engineering/Content, and contribute to quarterly strategy and traffic/revenue goals.

Lead SDET responsible for translating technical/architectural designs into low-level test solutions, mentoring engineers, developing and owning test automation frameworks, creating API/backend tests, extending API automation, supporting CI, and conducting performance, security, and scalability testing.

Lead QA for AI-driven products, designing QA strategy and frameworks (including LLM-as-a-judge), automating test case generation, overseeing model evaluation, coordinating with product and engineering, and managing and mentoring QA teams to ensure high-quality releases.

Lead a small data science team to research and build NLP/ML solutions (LLMs, RAG, vector search) for search, ranking, and content features; collaborate with product and engineering, estimate and run projects, mentor data scientists, and implement prompt-engineering and agentic workflows to improve user experience.

Lead design and implementation of agentic LLM-powered automation, build RAG and memory-augmented systems, optimize prompt and model performance, use embeddings and vector DBs, create evaluation frameworks, and collaborate cross-functionally to ship production features.

Lead a data science team to design, develop, and deploy ML/NLP and LLM-based solutions (search, recommendations, content generation/moderation). Convert business requirements into scalable models and pipelines, validate models, collaborate cross-functionally, and recruit and mentor data scientists.

Validate BI solutions by building test strategies, plans, and cases for ETL and BI components. Verify SQL queries, validate data sources and transformations, execute manual and automated tests, validate dashboards/reports, and produce test summary reports while collaborating with BI developers and business analysts.