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Sayari - Forward Deployed Engineer I (Remote, US)

Remote - USA$160k - $160k6d ago

Requirements

• 3 to 5 years in a client-facing technical role (forward deployed engineering, sales engineering, technical delivery, or technical consulting). • Production Python, including the data manipulation ecosystem (Pandas). • Deep SQL: writing and optimizing complex queries. • Hands-on experience integrating, testing, and supporting REST APIs. • Large-scale data processing with Spark, BigQuery, or Snowflake, and pipeline orchestration with Airflow or similar. • Working knowledge of AWS or GCP. • AI-assisted coding tools (Cursor, Claude, or similar) as a daily part of how you work. • Strong written and verbal communication. You explain technical work clearly to engineers, analysts, and senior stakeholders. • Problem solving in ambiguity, and fast uptake of new technologies and tools. • Bachelor’s or Master’s degree in a technical field. • Building with LLM APIs for analytical or automation tasks. • Containers (Docker, Kubernetes) and cloud deployment patterns. • BI and dashboarding tools (Looker, Tableau, Metabase). • Graph data technologies and their query languages. • Exposure to ML, NLP, or entity resolution. • Experience in high-stakes domains: AML and financial crime, supply chain risk, or national security. • How You Work • You are self-directed. You do not need someone to define every step. You spot gaps, ask the right questions, flag tradeoffs, and execute. You hold a high bar on output quality because the work you hand off represents Sayari to the customer. You take full accountability for what you deliver. • Logistics • Travel and in-office time: 25-30% combined. • Limitless growth and learning opportunities.

Responsibilities

• Scope and prove: run technical scoping and evaluation with customer teams, and confirm Sayari fits the workflow before delivery starts. • Scope and prove: • Implement: deploy risk screening, graph analytics and investigation workflows, and data integrations (APIs and feeds). Write production Python and SQL to do it. • Implement: • Deliver data: execute bulk data cuts and formatted data products (Parquet, CSV), set up and support API endpoints, and onboard customer pipelines: environment setup, data validation, integration testing. • Deliver data: • Keep deployments healthy: monitor usage and pipeline status, build dashboards that give customers and internal teams clear visibility, and resolve issues before they become churn risk. • Keep deployments healthy: • Build the playbook: follow and improve delivery playbooks and SOPs. Document your work clearly enough that another engineer can pick it up without a handoff call. • Build the playbook: • Feed the product: bring recurring customer needs and field findings back to core engineering. • Feed the product: