Software Engineer - Applied AI

As we onboard our first design partners, Cogent is launching the world's first AI cyber taskforce, which is composed of AI agents capable of human-caliber reasoning for cybersecurity tasks. We are looking for talented, ambitious AI/ML Engineers who are excited to build in the Applied AI space.

- Work closely with our design customers to design and launch our flagship AI agents that are capable of automating tasks in vulnerability management

- Understand business goals, product and technology strategies, and customer requirements and implement business-critical AI systems to achieve them

- Identify appropriate datasets and data representations to support system development

- Decompose existing enterprise security workflows into sub-tasks that can be modeled as an autonomous system

- Experiment with the latest advancements in long-term reasoning and planning to design systems that allows Cogent to evolve the data flywheel of our AI products from initially highly supervised to eventually autonomous and managed by exception

- Implement reusable system components for ranking, retrieval and search systems powered by LLMs for agentic automation

- Put in place frameworks to train, evaluate, and stress-test ML systems, and extend improvements on Cogent's Gen AI platform

- Stay on top of and when appropriate, propose incorporating cutting edge developments in ML and Gen AI into Cogent's AI systems

- Actively contribute to Engineering Excellence, Operational Excellence and Recruiting initiatives

- Multiple years of relevant experience in developing and deploying AI-driven systems, with a proven track record of architecting practical, production-grade solutions that solve real-world problems

- Expertise in machine learning, deep learning, and AI models, with a deep understanding of how to apply these technologies to build scalable, performant systems in production environments

- Experience with designing and deploying agentic systems and autonomous agents, as well as integrating these AI components into larger applications or products

- Ability to address and navigate real-world scale and performance challenges, ensuring that AI models and systems are efficient, robust, and performant under production constraints

- Familiarity with cutting-edge AI technologies, including reinforcement learning, natural language processing, computer vision, and large-scale generative models

- Proven ability to work iteratively and collaborate with cross-functional teams to evolve AI models and systems that meet evolving product needs and user expectations

- Passion for staying at the forefront of AI advancements, continuously learning and applying emerging techniques to improve product performance and drive innovation