Senior AI Systems Engineer As a Senior AI Systems Engineer, you will lead the design and implementation of cutting-edge AI systems. You will be responsible for producing detailed blueprints, specifying and overseeing pipeline construction, defining strategies for retrieval-augmented generation, and guiding teams building models for contract auditing, price forecasting, and portfolio optimization. You will work closely with cross-functional teams to design and deploy end-to-end machine learning and AI pipelines into production, covering service hosting, containerization, and cloud infrastructure. Additionally, you will establish coding standards, testing frameworks, and review processes for AI/ML workflows. - Key Responsibilities: - Lead design sessions and produce detailed AI system blueprints. - Specify and oversee construction of end-to-end LLM/ML pipelines. - Define strategies for retrieval-augmented generation, vector databases, and knowledge graphs. - Guide teams building models for contract auditing, price forecasting, and portfolio optimization. - Design and oversee the end-to-end deployment of machine learning and AI pipelines into production. - Establish coding standards, testing frameworks, and review processes for AI/ML workflows. - Cross-functional collaboration and mentorship. The ideal candidate will have 8+ years of professional software development experience, with 5+ years in production ML/AI systems. They will have a proven track record as an AI Architect or technical lead, able to envision complex systems and drive them to production. The candidate should also have demonstrated experience in AI research & development, publishing, and prototyping novel approaches. Requirements - 8+ years of professional software development experience. - 5+ years in production ML/AI systems. - Proven track record as an AI Architect or technical lead. - Demonstrated experience in AI research & development. - Experience with LLMs (locally hosted and API-based), plus hands-on RAG/vector search experience. - Fluent in designing microservices and REST APIs for AI inference at scale. - Strong systems-level thinking and product mindset. - Experience with cloud-native platforms (AWS, GCP, Azure), Docker, and Kubernetes. - Excellent verbal and written communication skills. What We Offer: Competitive compensation, budgets for education, fitness, and team activities, flexible working arrangements.