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Tech Stack
Tools & technologiesAWSAzureCloudDockerPython
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- 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.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Generative AIretrieval-augmented generation (RAG)semantic searchdocument intelligencePythoncloud-native solutionscontainerizationAI orchestration frameworksAI architecture designenterprise data integration
Soft Skills
technical leadershipmentoringcollaborationproblem-solvingcommunication
Certifications
Bachelor's degree in Computer ScienceMaster's degree in Data ScienceMaster's degree in Engineering
