C2C jobs AI Enginner in Location: Sunnyvale, CA

AI Enginner
Location: Sunnyvale, CA (5x/ week onsite)
Duration: 6 months

Oracle PL/SQL, Data Migration, Load / Performance testing. Java, Rest APIs
Build and maintain RESTful APIs using FastAPI, Django REST Framework, and Flask, following established performance, security, and coding standards.
Develop modular system components and contribute to improving application reliability, performance, and maintainability.
Assist with data processing and asynchronous workflows using Pandas, NumPy, and frameworks such as Celery or PySpark.

Role Descriptions: Build and deploy production-grade Retrieval-Augmented Generation (RAG) pipelines using vector databases| and contextual reranking to deliver domain-specific recommendationsDesign and implement multi-agent AI workflows with LangChain| ReAct-style tool-calling| and agentic reasoning patterns to automate problem interpretation and solution generation.Develop ML forecasting systems by benchmarking time-series models | engineering temporal features| and implementing automated retraining pipelines to predict business outcomes with high accuracy.Build data pipeline using SQL and Python| applying feature engineering| categorical encoding| and dimensionality reduction for datasets.

Create analytics dashboards in Power BI that integrate ML model outputs| SQL pipelines| and business KPIs to drive strategic decision-making and market expansion initiatives.Develop frontend and backend solutions by creating APIs that link ML models to frontend applications| using Git and automated deployments to ship features reliably.Serve as a technical bridge between AI research| engineering teams| and business stakeholders translating AI capabilities into applications Ensure AI systems align with product goals while maintaining reliability and interpretability.

Essential Skills: Build and deploy production-grade Retrieval-Augmented Generation (RAG) pipelines using vector databases| and contextual reranking to deliver domain-specific recommendationsDesign and implement multi-agent AI workflows with LangChain| ReAct-style tool-calling| and agentic reasoning patterns to automate problem interpretation and solution generation.

Develop ML forecasting systems by benchmarking time-series models | engineering temporal features| and implementing automated retraining pipelines to predict business outcomes with high accuracy.Build data pipeline using SQL and Python| applying feature engineering| categorical encoding| and dimensionality reduction for datasets.Create analytics dashboards in Power BI that integrate ML model outputs| SQL pipelines| and business KPIs to drive strategic decision-making and market expansion initiatives.Develop frontend and backend solutions by creating APIs that link ML models to frontend applications| using Git and automated deployments to ship features reliably.

Serve as a technical bridge between AI research| engineering teams| and business stakeholders translating AI capabilities into applications Ensure AI systems align with product goals while maintaining reliability and interpretability.