Front-End Developer
E-talentnetwork
Calstrs Technology Services TeamThe CalSTRS Technology Services (TS) Branch delivers technology products, services, and business solutions which support all information technology systems throughout the organization including implementation of enterprise projects. TS programs and projects utilize the System Development Life Cycle (SDLC) methodology and Agile Development guidelines. The goal of this engagement is to construct a team of technical resources, with all the necessary skillsets collectively, for maintaining and advancing CalSTRS' IDW platform with GenBI/ AI/ML capabilities, as well as designing/building additional GenBI solutions or use cases that will be deployed onto the IDW platform.Minimum Technical Qualifications:At least five (5) years of experience in front-end UX/UI design for analytics dashboards and highly interactive reporting.At least four (4) years of experience in development with React for or building scalable, highly customized production-grade user interfaces.At least two (2) years of experience in front-end development with Chainlit or Streamlit for AI/ML or GenAI solutions with complex state management & data handling (e.g., real-time updates; UI states for loading, retries, and partial responses).At least two (2) years of experience in latency handling and async UX patterns, explainable AI interfaces (confidence, sources, disclaimers), and prompt design basics.At least two (2) years of hands-on experience and proven ability to build chat interfaces (streaming responses, token handling), and AI-assisted workflows (autocomplete, summarization, recommendations).Desirable Technical Qualifications:Holding technical certifications in the areas of:AWS certificationsSnowflake certificateBI certifications (Power BI, Tableau)AI/ML or GenAI-related coursework or credentialsAt least five (5) years of experience in data engineering, data warehousing, or BI analytics.At least three (3) years of experience working with AI/ML or GenAI technologies to design and build AI/GenAI solutions using cloud services such as AWS, Snowflake, or Azure.Practical hands-on experience using OpenAI APIs or similar LLM platforms, building natural language to programming languages such as SQL/query, designing prompt strategies for business insights, and prompt engineering to guide system behavior.Experience in developing semantic models supporting natural language querying and AI-driven analytics (i.e., GenBI); statistical analysis, predictive analytics, and optimization.Have a bachelor's degree in computer science, computer engineering, or related fields from an accredited or government sanctioned college/university. CalSTRS may request a copy of the diploma/degree.The proposed onsite project person will be able to adhere to the hybrid working model by working on-site 2 to 3 business days per week at CalSTRS Headquarters, West Sacramento, CA.Description of Services The Tech-Team will be primarily managed by and work directly with the CalSTRS Investment Data Solutions division daily. Collectively, this Tech-Team is expected to provide full-stack development coverage, as well as the ongoing support to maintenance and operations (M&O) of the IDW and use cases deployed on it. The scope of key responsibilities and activities include but is not limited to the following:Effectively apply User Interface (UI)/ User Experience (UX) design principles for designing and building analytics dashboards with technologies such as Chainlit, Streamlit, and React.Create interactive reporting and storytelling based on data visualization best practices, and humancentered design.Leverage Out-of-Box (OOB) services/functions/APIs (e.g., calling SNOWFLAKE.CORTEX functions via SQL or configuring AWS Bedrock Knowledge Bases) to accelerate the design and implementation of use cases.Build automated tests to ensure the platform's Text-to-SQL engine isn't hallucinating incorrect numbers.Perform continuous prompt engineering to guide and finetune the platform's system behavior.Execute statistical analysis, predictive analytics, optimization; conduct AI/ML model prototyping with ML frameworks such as TensorFlow, PyTorch, scikit-learn.Apply expertise in platform-specific semantic layers or dbt (Data Build Tool), advanced SQL and dimensional modeling (Star Schema), and cloud ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI)Implement containerization and orchestration (Docker, Kubernetes).Operate CI/CD pipelines for ML and data workflows, data integration, cleaning, and transformation processes.Responsible for monitoring, tuning, and logging for AI/ML and GenBI solutions, Extract, Transform, Load (ETL)/ Extract, Load, Transform, (ELT) pipelines (e.g., Airflow, Matillion), cloud data warehouses & lakes (e.g., Snowflake, Redshift, BigQuery, Azure Synapse), and cloud infrastructure automation (e.g., Terraform, Ansible).Continuously enhance and verify that the entire IDW ecosystem/solution are cost-effective, secure, and scalable.Provide technical leadership, solution guidance to project teams in support of solution design and development, and act as a technical liaison among Investment stakeholders, technical developers, 3rd party vendor teams and tech support.Apply vast experience and multidisciplinary expertise in AI Infrastructure & Agentic Workflows/Orchestration, Generative AI Design Patterns, Cloud Strategy & FinOps, and Security & Compliance (AI Governance) to support key Investment's initiatives.Analyze solutions and technologies and make recommendations based on knowledge of CalSTRS Investment Branch's current and future needs.Proactively monitor and assess strategic direction of solution vendors, technology and market trends, and determine their potential impact and value to the IDW; prepare presentations, documents, diagrams, models, and other artifacts as required to communicate analysis, recommendations, or designsAll qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
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