Senior Applied AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, prototype, and develop AI capabilities that are production-ready, enhancing reasoning, accuracy, explainability, and developer productivity.

• Assess emerging large language models (LLMs), multimodal frameworks, agent architectures, and AI methodologies to uncover opportunities for platform enhancement.

• Quickly prototype innovative AI functionalities and transition successful trials into operational use.

• Enhance autonomous and multi-agent workflows through prompt engineering, optimization of reasoning, memory techniques, tool selection, and context management.

• Ongoing refinement of Retrieval-Augmented Generation (RAG) pipelines, retrieval approaches, embeddings, reranking, and grounding methods.

• Boost the quality of AI responses through experimentation, benchmarking, and iterative enhancements.

• Create evaluation frameworks to assess accuracy, groundedness, explainability, latency, and overall AI performance.

• Construct benchmark datasets, automated evaluation pipelines, and performance metrics for AI systems in production.

• Investigate AI failures, hallucinations, retrieval deficiencies, and reasoning mistakes to foster continuous improvement.

• Collaborate with software engineers to enhance knowledge ingestion, document processing, semantic search, embeddings, and enterprise knowledge management.

• Devise strategies that optimize retrieval quality across extensive technical documentation and source code repositories.

• Enhance the methods AI agents use to discover, organize, and reason about enterprise knowledge.

• Work closely with AI architects, platform engineers, software engineers, and front-end engineers to boost the overall intelligence of the platform.

• Share research insights, experimental outcomes, and engineering suggestions with cross-functional teams.

• Assist in establishing best practices for experimentation, evaluation, and AI quality across the organization.

⛳️ Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Engineering, Data Science, or a related technical field (or equivalent professional experience).

• Over 5 years of experience in software engineering, applied AI, machine learning, or AI systems development.

• Proven experience in developing production AI applications utilizing Large Language Models (LLMs).

• Experience in designing and optimizing Retrieval-Augmented Generation (RAG) systems.

• Familiarity with prompt engineering, embeddings, semantic search, vector databases, and knowledge retrieval.

• Experience in evaluating AI model performance and implementing experimentation frameworks.

• Proficient programming skills in Python and familiarity with modern software engineering methodologies.

• Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.

• Experience incorporating AI coding assistants in your daily workflow.

• Understanding of REST APIs, cloud-native applications, and distributed software systems.

• Strong analytical, problem-solving, and communication abilities.

• A keen intellect and curiosity regarding AI systems and their functionalities.

• A profound passion for experimenting with emerging AI techniques.

• Background in evaluation, explainability, and ongoing improvement.

• Demonstrated success in tackling complex technical challenges and collaborating across various disciplines.

🏝️ Benefits

• The opportunity to support high-visibility federal missions.

• A culture that prioritizes innovation, growth, and collaboration.

• Access to state-of-the-art tools and technologies.

• Comprehensive benefits for you and your family.

• A career trajectory that rewards ambition and performance.