Overview
As a Senior Applied AI Engineer, you will play a critical role in designing and implementing agentic AI systems that operate under strict reliability and performance requirements in high-stakes environments. Collaborating with a team of engineers, you will take on end-to-end technical ownership of production systems, ensuring that they meet stringent standards for decision-making. This position offers a unique opportunity to contribute directly to innovative AI solutions that support defense, national security, and commercial organizations with complex data challenges.
Responsibilities
- Build multi-agent AI systems from the ground up, implementing necessary frameworks and infrastructure.
- Write clean, tested, maintainable production-grade code while prioritizing reliability and performance.
- Integrate large language and vision-language models into reasoning and execution pipelines.
- Deploy systems in cloud, on-premises, and offline environments, considering security and reliability constraints.
- Own the full data pipeline, from ingestion to inference, ensuring comprehensive control over system functionality.
- Establish evaluation and observability mechanisms to assess operational behavior and performance metrics.
- Serve as a technical authority for agentic AI, guiding other engineers in design patterns and implementation practices.
Requirements
- Minimum of 6 years of professional software engineering experience, including significant work with LLM-based or agentic systems.
- Strong proficiency in Python with hands-on experience in LLM frameworks such as LangGraph, LangChain, or Haystack.
- Demonstrated ability in designing and deploying AI/ML systems into real-world production environments.
- Experience managing large multi-modal datasets and implementing efficient search and retrieval mechanisms.
- Familiarity with deployment environments, including Docker, Git, and cloud platforms (AWS preferred).
- Understanding secure deployment patterns and best practices for offline and air-gapped systems.
- Proven track record of owning technical projects end-to-end and maintaining documentation for knowledge transfer.