Data Platform Engineer (AI)

Location: Remote in the U.S.; San Jose office (HQ). The role is remote, with a preference for candidates based in the Bay Area.

Salary: $200,000–$250,000 annually, plus equity.

Company

Build multi-agent AI systems that automate complex enterprise workflows across platforms including SAP, Salesforce, Workday, Snowflake, and MuleSoft.

What you will do

• Build data platform services and APIs for data access, query execution, ingestion, and synchronization.
• Develop reusable connector frameworks and abstractions for different enterprise systems and access patterns.
• Optimize querying and data movement through partitioning, parallelism, and effective memory and storage management.
• Build orchestration, retries, checkpointing, and observability to support reliable workload recovery and data correctness.
• Take platform capabilities from design through production in collaboration with product and engineering teams.

Requirements

• At least 2 years of experience as a Data Platform Engineer.
• Strong Python and SQL skills, with experience building maintainable, tested production software.
• Experience developing backend services, data infrastructure, or data platform components beyond configuring pipelines.
• Understanding of relational databases, query optimization, data formats, and data materialization tradeoffs.
• Experience with concurrent or distributed workloads, failure handling, resource management, and performance debugging.
• Ability to investigate unfamiliar systems and turn complex requirements into practical designs.

Nice to have

• Experience with analytical query engines, lakehouse technologies, workflow orchestration, enterprise-system integrations, or containerized infrastructure.
• Experience building connector libraries, developer-facing APIs, or shared engineering platforms.
• Familiarity with AWS, Azure, or GCP, including networking, storage, IAM, and infrastructure as code.

Culture & Benefits

• Work on AI products addressing complex enterprise problems.
• Work at the intersection of AI, ERP systems, and automation.
• High ownership, high impact, and direct influence on product direction.
• Collaborate with a technical, customer-focused team.
• Equity included in the compensation package.