Design and implement enterprise Generative AI services and knowledge copilots.
Build retrieval‑augmented generation (RAG) pipelines leveraging enterprise data.
Implement enterprise semantic search, knowledge indexing, and document intelligence systems.
Develop reusable frameworks for enterprise prompt management, evaluation, and AI observability.
Design and deploy AI agents capable of planning and executing multi‑step workflows across enterprise systems.
Implement multi‑agent orchestration architectures where specialized agents collaborate to complete business tasks.
Enable AI agents to interact with internal APIs, databases, and business applications while maintaining governance controls.
Integrate AI systems with enterprise data platforms including Snowflake and its AI capabilities such as Snowflake Cortex.
Implement AI guardrails, safety filters, and governance controls for enterprise GenAI usage.
Design human‑in‑the‑loop review workflows for critical insurance decisions.
Ensure compliance with privacy, security, and regulatory requirements.
Monitor AI and agent outputs for reliability, bias, and quality.
Provide technical leadership in the adoption of GenAI and Agentic AI across the enterprise.
Partner with enterprise architecture and data teams to define AI platform standards.
Mentor engineers and contribute to reusable enterprise AI frameworks.
Help scale GenAI adoption across multiple business units.

A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or equivalent.
6+ years of experience in Software engineering, AI engineering, or data platform development.
Experience designing and delivering enterprise Generative AI applications.
Hands-on experience with enterprise data and ML platforms such as Snowflake or Databricks.
Experience building cloud-native solutions on AWS, Azure or Google Cloud.
Strong Python programming skills.
Experience building RAG pipelines, semantic search and AI driven workflows.
Familiarity with AI agents and orchestration frameworks (e.g., LangChain, LlamaIndex, or similar).
Experience integrating AI with APIs, enterprise applications, and business processes.
Ability to design scalable AI architectures with strong governance, security ad privacy.
Experience working with structured and unstructured enterprise data.
Practical experience with containerization technologies, including Docker.

Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.
Hybrid flexible work model.
Outstanding career development opportunities.
We’ll support your professional development education.
Competitive vacation package with the option to purchase 5 extra days off per year.
Employee-driven programs focused on gender, LGBTQ+, origins, diversity, and inclusion.
Corporate wellness programs to support our employees’ physical and mental health.

Senior GenAI Engineer

Key skills