Top Tech Jobs & Startup Jobs

Design, build, and deploy GraphQL subgraphs: analyze requirements, propose and design schemas, create prototypes, implement resolvers and unit tests, set up CI/CD pipelines with security tooling, enable UI/QA integration, support UAT, and monitor production.

Designs, develops, tests, and supports Java/Java EE applications across the full SDLC. Creates user interfaces, selects design methodologies and toolsets, writes code, troubleshoots multi-environment issues, and produces documentation and support tools. Works with relational databases, ORM, Spring and web frameworks and integrates logging/monitoring solutions.

Join the Machine Learning Data Enablement team to build scalable, production-ready data pipelines for ML models. Collaborate with data scientists and ML engineers to deliver curated datasets, using Python and SQL and modern data tooling (Snowflake, dbt, SageMaker). Onsite role with high visibility and opportunity for growth.

Design, build, and maintain automated test frameworks and scripts. Lead test strategy, planning, and execution across functional, load, integration, security, server-side, and ETL testing. Create test artifacts, run automated tests, analyze results, report defects, participate in CI/CD, code reviews, and agile ceremonies, and drive issue resolution.

Lead development and deployment of generative AI models (LLMs, GANs), design and optimize model architectures, build data pipelines, implement MLOps, evaluate and improve model performance, ensure ethical AI practices, integrate solutions with cross-functional teams, and mentor team members.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Design, build, and maintain the company's scalable platform and public APIs. Ensure uptime, performance, security, and automation across cloud and on-prem systems. Work with big-data technologies, DBAs, data scientists, and operations to implement ETL, monitoring, deployment strategies, and production-scale administration.

Design, build, and maintain scalable enterprise data pipelines and Snowflake data warehouse solutions. Develop DBT models, modernize IBM DataStage ETL, integrate legacy systems, optimize SQL and warehouse performance, ensure data quality and governance, troubleshoot production issues, support BI and resiliency, and collaborate with architects and stakeholders in an Agile environment.

Design and implement causal inference and causal ML solutions, measure treatment effects and business impact, build production-ready ML pipelines, integrate Generative AI where applicable, partner with product teams, present findings, and mentor peers.

Design, develop, test, and maintain Java-based enterprise applications and scalable REST APIs/microservices using Spring Boot. Work with relational databases, unit/integration tests, CI/CD, version control, and participate in Agile ceremonies. Support cloud deployments, debugging, code reviews, and collaborate with cross-functional teams.