Forward Deployed AI / Data Engineer

We are seeking a hands-on engineer who can work directly with customers, understand complex requirements, and rapidly build production-ready software, data, and AI solutions.

Key Responsibilities

• Translate customer requirements into practical technical solutions.
• Build and deploy applications, APIs, backend services, and data pipelines.
• Develop ETL/ELT workflows, data models, schema mappings, and bulk data-processing solutions.
• Build GenAI applications including LLM agents, RAG pipelines, tool-calling workflows, and AI automation.
• Integrate enterprise data, databases, APIs, cloud platforms, and AI models.
• Develop primarily in Python and, where needed, TypeScript.
• Troubleshoot application, API, infrastructure, integration, and data issues.
• Follow strong engineering practices for testing, CI/CD, monitoring, security, and documentation.
• Work directly with customers and senior stakeholders throughout discovery, implementation, and production deployment.

Required Skills

• Strong hands-on software engineering experience.
• Strong Python development skills.
• Solid data engineering experience including ETL/ELT, data modeling, schema mapping, and pipelines.
• Experience designing and integrating REST APIs and backend services.
• Hands-on experience with LLMs / Generative AI.
• Experience with AI agents, RAG, tool calling, LLM applications, or AI workflow automation.
• Strong debugging, problem-solving, and communication skills.
• Ability to independently turn ambiguous requirements into working solutions.
• U.S. Citizenship required.
• Must be based in or willing to work in the Washington, DC metro area.
• Hybrid availability with 2 3 days per week onsite/customer-site presence.

Preferred

• Background as a Forward Deployed Engineer, Solutions Engineer/Architect, Technical Consultant, or customer-facing Software/Data Engineer.
• Federal government, defense, intelligence, national security, or mission-critical experience.
• AWS, Azure, or GCP experience.
• Experience with technologies such as Snowflake, Databricks, Spark, Kafka, Airflow, or dbt.
• Experience with vector databases, embeddings, retrieval systems, and LLM frameworks.
• Experience deploying AI applications to production.
• Familiarity with AI evaluation, human-in-the-loop workflows, enterprise security, authentication, authorization, and data governance.