Staff AI Engineer

Requirements

• Strong opinions about best practices for agentic engineering and AI coding tools, and enthusiasm for further developing best practices.
• Experience mentoring engineers and developing communities of practice within engineering groups.
• Comfort and competence deploying features into AWS cloud infrastructure.
• Master's degree or PhD in Computer Science, Engineering, or related field
• How We Work
• We're a hybrid team that values autonomy, mission impact, and craftsmanship in equal measure. Here's what that looks like in practice:
• We own our work end-to-end. Engineers here don't just write code - they help shape the problem, design the solution, and care about what happens after it ships. You'll have genuine ownership over meaningful ML systems, not just tickets in a queue.
• We build with rigor and move with purpose. We believe quality and velocity aren't at odds. We are looking for developers fully leaning into agentic engineering and AI coding tools to increase their velocity as well as their quality.
• We collaborate openly across disciplines. Our ML engineers work closely with software engineers and product stakeholders. Perspectives from across the org sharpen our thinking - you'll both contribute to and learn from those conversations regularly.
• We trust each other with the hard stuff. You'll be working on problems where the answers aren't obvious. We want people who are comfortable with ambiguity, willing to surface concerns early, and confident enough to push back when something doesn't seem right.
• Why join this team:
• Immediate Mission Impact: Join a small, agile team where your contributions will have a direct, tangible impact on Strider's mission from day one.
• Data-Rich Environment: Leverage our large, diverse, proprietary datasets to drive innovation and exploration in machine learning and AI.
• Continuous Learning: Benefit from our commitment to your personal and professional growth, whether it's mastering new technical skills or learning a new language.
• Culture of Innovation: Be part of a forward-thinking team that values innovative thinking and the continuous improvement of our practices and solutions.

Benefits

Additional Information

Strider Technologies delivers strategic intelligence that helps organizations make faster, more confident decisions in an increasingly complex global environment. Using cutting-edge AI and proprietary methodologies, we transform open-source data into actionable insights that help protect technology, talent, and supply chains from nation-state risks. We are looking for an exceptionally motivated Staff AI Engineer to join Strider's Context Engineering team. Context Engineering exists to help shape, stage, and prioritize data for consumption by our analysts, customers, and agentic analytical production processes. We are looking for candidates who are comfortable working across our full data processing pipeline and are motivated by solving problems and having mission impact. We want individuals who are excited to use AI to amplify their leverage and are enthusiastic about the evolving practice of software and agentic engineering. You will: Build and own services and features to support our Context Engineering organization, focusing on hybrid data search capabilities (using ElasticSearch and S3Vectors) at million to billion document scale. Optimize a variety of LLM-based data processing tasks: for example, entity disambiguation, document quality and relevance scoring, text extraction tasks. Design technical solutions and provide feedback on design documents and architectural decisions across the organization. Participate in code reviews and help improve practices for AI-assisted code review. What you need to be successful: Bachelor's degree in Computer Science, Engineering, or related field 10+ years of experience Track record of setting technical direction and executing beyond the small team level. Demonstrated examples of making architectural/technical bets that paid off, or course-corrected when they didn't. Experience shipping features and solutions that use LLMs in data heavy environments. Experience with frontier model SDKs (OpenAI, Anthropic, etc.), open-source model providers and frameworks, agentic frameworks. Ability to communicate complex technical concepts and engage with senior stakeholders across disciplines (engineering, product, executives). Self-motivated with excellent problem-solving skills and a strong attention to detail.

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