Senior Engineer

Curinos is currently seeking a Senior Engineer to join the Data & AI Platforms group. This team owns the shared data ecosystem upon which our B2B SaaS applications are built and is responsible for building a platform to power our generative AI applications. As a company that specializes in data-driven insights, the reliability, scalability, and effectiveness of our data & AI platforms are integral to our product offerings.

Responsibilities:

You’ll work with a diverse team of talented engineers and product managers to build our next generation data and AI platforms, support migration of products from legacy infrastructure, and help product engineering teams leverage the platforms to launch new products and build new genAI applications. Typical responsibilities will include:

• Designs and builds AI platform functionality to support efficient development of production quality multimodal generative AI applications, including tooling to support accuracy, evaluation, and guardrails
• Designs and builds data platform functionality to support scalable and reliable data ingestion, storage, validations, governance, monitoring & observability, ELT patterns, and more
• Implements software, data, and ML/AI engineering best practices, including related to software development lifecycle, testing, scaling, performance optimization, and more
• Documents key Platform approaches and frameworks for utilization across the organization
• Proactively identifies and implements new technologies and tools to improve efficiency and productivity
• Conducts code reviews and provides feedback to help team members
• Supports product teams in adopting platform tools and frameworks
• Provides input and participates in agile ceremonies like standup, planning, grooming, retro etc.

Base Salary Range: $110,000 - $160,000 (plus bonus)

Requirements

• Python and SQL advanced proficiency
• Spark experience required
• Databricks experience preferred
• Java or Scala proficiency is a plus
• Generative AI (LLMs, RAG, AI agents) experience preferred; other ML experience also a plus
• Strong grasp of data engineering best practices, including ETL/ELT, data monitoring & observability, and data validations
• Experience working with big data, including scaling data processing and distributed computing
• Experience with production support
• Minimum of 3 years of professional experience – 4+ years preferred
• Self-discipline and willingness to learn new skills, tools and technologies
• Solid verbal and written communication skills