Staff AI Engineer (Data & Intelligence function)

Accountabilities:

• Design, build, test, and ship production AI systems as an active hands-on engineering contributor.
• Lead the development of high-performance customer context retrieval capabilities using semantic search, indexing, embeddings, vector search, hybrid retrieval, and knowledge graph approaches.
• Build systems that allow agents to identify customers and retrieve comprehensive context efficiently from multiple data sources.
• Develop inference and signal-processing layers that read from an Iceberg-based lakehouse, generate scored insights, and expose reliable signals through contracts that other teams can consume.
• Transform signals such as churn risk, usage or entitlement mismatches, and expansion opportunities into automated workflows that drive appropriate actions, incorporating human review where required.
• Select the appropriate technical approach for each workload, balancing large language models, smaller specialized or fine-tuned models, and deterministic software while managing inference costs.
• Establish evaluation and observability practices for AI systems, including tracing, prompt and model versioning, dataset-driven testing, and evidence that signals are reliable before they are acted upon.
• Define reusable engineering patterns and shared capabilities that enable other teams to build effectively on the organization’s AI and data infrastructure.
• Partner with engineering and business leaders to translate strategic objectives into scalable, production-ready systems.
• Adapt quickly to unfamiliar technical contexts, technologies, codebases, and evolving AI frameworks while maintaining a strong focus on delivering useful production outcomes.

Requirements:

• You have 8+ years of software engineering experience, including at least 3 years shipping AI or machine learning systems into production.
• You have strong software engineering fundamentals and deep proficiency in at least one language used for AI and data engineering, with Python being the primary language for ML and insights.
• You are highly proficient with data at scale, including advanced SQL, a transformation framework such as dbt, and distributed query engines operating over lakehouse or warehouse storage.
• You understand query optimization, partitioning, cost management, and the practical challenges of working with large-scale data platforms.
• You have production experience with retrieval and context engineering, including embeddings, vector search, hybrid or graph retrieval, and measuring retrieval quality and effectiveness.
• You have experience modeling entities and relationships across multiple data sources, particularly where this supports customer context and intelligent systems.
• You have built and operated agentic systems and durable workflows using tool calling, state, memory, and human-in-the-loop patterns, with experience in Temporal, LangGraph, or equivalent technologies.
• You understand how to evaluate and observe AI systems through tracing, prompt and version management, dataset-driven testing, and other appropriate engineering practices.
• You have cloud deployment experience, preferably with AWS, including containerized services and responsibility for managing inference costs.
• You hold a B.S. in Computer Science or have equivalent practical experience.
• You have experience creating shared data or ML capabilities that other engineering teams can build upon.
• Experience with smaller or fine-tuned models, model distillation, high-volume observability data, OpenTelemetry, data governance, lineage, access controls, or data residency is highly valuable.
• Experience in enterprise SaaS, CMS environments, or complex digital platforms is beneficial.
• You are comfortable using AI-assisted development tools such as Claude, Cursor, or GitHub Copilot and technologies such as MCP to connect intelligent systems with real-world tools and services.
• You communicate complex AI system designs effectively to both technical teams and executive stakeholders.
• You have a strong senior individual contributor track record, with a reputation for high-quality code and system design and an ability to mentor others through technical leadership and example.
• You demonstrate adaptability, intellectual curiosity, strong ownership, and a builder mentality, with the ability to use AI as an integral part of your engineering workflow.

Benefits:

• Competitive healthcare coverage designed to support employees and their families.
• Wellness programs and resources supporting physical and mental well-being.
• Flexible time-off policies that allow employees to take time away when needed.
• Parental leave and family-focused support.
• Recognition programs that celebrate employee contributions and achievements.
• Opportunities to work with large-scale data platforms, AI systems, agentic workflows, and modern cloud technologies.
• Exposure to complex enterprise data, observability, retrieval, inference, and intelligent automation challenges.
• Significant opportunity to influence shared engineering capabilities and AI development practices across multiple teams.
• A hands-on environment that supports experimentation, continuous learning, and rapid iteration.
• Career development opportunities within a global technology organization focused on innovation and AI-enabled transformation.