Altana Offices

Altana is headquartered in New York and has 4 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Flexible

U.S. Office Locations

HQ

New York

25 Kent Avenue, New York, NY, United States, 11249

Boston

1 Beacon St , Boston, MA, United States, 02108

San Francisco

San Francisco, California , United States

Washington

801 18th Street, NW Suite 400, Washington, DC, United States, 20006

Recently posted jobs

11 Hours AgoSaved
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Hybrid
2 Locations
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Artificial Intelligence • Machine Learning • Software
Support public-sector sales of Altana’s AI-powered trade and economic security platform. Translate technical capabilities into customer value through presentations, demos, whiteboarding, and original data analysis. Partner with sales, product, engineering, marketing, and customer stakeholders to identify use cases, inform product development, and communicate customer needs. The role requires knowledge of public-sector operations, international trade, defense, or national and economic security, plus proficiency in Python and/or SQL.
YesterdaySaved
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Hybrid
Brooklyn, NY, USA
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Artificial Intelligence • Machine Learning • Software
Lead the technical direction, architecture, and roadmap for production agentic AI systems processing global trade data. Build ingestion, document understanding, entity resolution, inference, evaluation, observability, and feedback pipelines. Adapt and post-train large language models, improve system reliability, mentor senior engineers, shape ML hiring standards, and collaborate with product, engineering, data science, and customers to deliver practical risk, compliance, and enforcement capabilities.
YesterdaySaved
Easy Apply
Hybrid
Brooklyn, NY, USA
Easy Apply
Artificial Intelligence • Machine Learning • Software
Lead the technical direction and development of production machine learning and agentic AI systems for global trade risk, compliance, and enforcement. Responsibilities include designing ingestion and inference pipelines, adapting and post-training LLMs, building evaluation and observability systems, mentoring engineers, setting architecture across teams, and partnering with product and customers to deliver measurable capabilities.