Forward Deployed Engineer, CE (Evergreen)

Role overview

This evergreen posting invites candidates to express interest in a Forward Deployed Engineer role tied to a commercial intelligence platform used for economic security and risk investigations. Engineers are embedded directly inside strategic client environments to deliver the "last mile" of product impact on high-stakes missions such as financial crime, supply chain disruption, and national security threats. The position blends engineering, strategy, and field operations—spanning hands-on coding, architectural design, data pipeline work, and executive-level briefings—and suits people who thrive on ambiguity and extreme ownership.

Responsibilities

- Embed in client technical ecosystems to understand workflows, environments, and mission needs; design, build, and ship production-grade Python applications and SQL pipelines using platform APIs. - Own the full technical lifecycle of strategic deployments, from discovery and architectural design through implementation and operationalization. - Act as the primary technical authority for clients: lead deep-dive workshops, debug complex systems, and advise on how to leverage the platform for real-world investigations. - Translate ambiguous mission requirements into concrete solutions, including data pipelines into client persistence layers (e.g., Snowflake, Databricks), custom scripts, and AI/ML prototypes. - Channel frontline feedback into core engineering, turning bespoke client solutions into scalable platform-wide features.

Requirements

- 5+ years in a client-facing technical role such as Forward Deployed Engineer, Sales Engineering, Solutions Architecture, or Technical Consulting. - Demonstrated ability to write clean, production-ready code, with strong proficiency in Python and its data ecosystem (Pandas, etc.). - Deep fluency writing and optimizing complex SQL. - Excellent problem-solving skills and comfort navigating ambiguous, complex scenarios. - Relentless drive, intellectual curiosity, and willingness to learn new technologies quickly in unfamiliar environments. - Bachelor's or Master's degree in a technical field strongly preferred.

Nice to have

- Practical experience with AI, including prompting LLMs or using their APIs to build analytical solutions. - Experience deploying solutions on AWS, GCP, or Azure, plus familiarity with Docker or Kubernetes. - Familiarity with the modern data stack (Snowflake, Databricks) and workflow orchestrators (Airflow, Prefect). - Exposure to graph data technologies such as Neo4j or TigerGraph. - Machine learning experience in NLP or entity resolution. - Passion for high-stakes domains such as AML/Financial Crime, Supply Chain Risk, or National Security. - Willingness to travel up to 30%.

Benefits and work setup

- Target base salary of $160,000–$180,000 USD plus commission and equity, with final offers influenced by location, market, and experience. - 100% employer-paid medical, vision, and dental coverage for employees and dependents. - Generous time off: all US federal holidays, a winter office closure (December 24–31), 18 PTO days, and 10 sick days. - Additional benefits include a 401k match up to 5%, 100% paid life insurance up to $100,000, and parental leave. - Collaborative culture with emphasis on diversity, equity, inclusion, and growth opportunities.