Teams at Blend360

Develop and deploy machine learning and statistical models for customer, marketing, campaign, and business analytics. Build predictive models for targeting, propensity, response, churn, and customer behavior using Python, SQL, Databricks, and PySpark. Perform feature engineering, validation, tuning, and evaluation on large-scale datasets; translate business questions into analytical solutions; communicate insights to stakeholders; productionize solutions; and mentor junior data scientists.

Design and develop scalable backend services using C# and SQL, build cloud-native applications on AWS, and support data migrations, system integrations, reporting, and analytics. The role requires strong software architecture, database design, technical decision-making, and collaboration with cross-functional teams. Engineers will work with Snowflake, SQL Server, Terraform, and occasionally React, TypeScript, and Python while independently solving complex technical challenges.

Leads the technical direction, architecture, quality, and growth of an AI Engineering practice. Designs production AI systems, guides major client engagements, conducts design reviews, resolves complex engineering challenges, shapes proposals and delivery plans, and develops senior technical talent. The role remains hands-on with Python, AI architectures, retrieval, agentic pipelines, evaluation, scalability, reliability, and observability. It also requires client-facing leadership, commercial awareness, capability planning, and experience with Databricks and Azure OpenAI.