Must have:

• 6+ years of experience in software engineering, intelligent systems, or applied machine learning, including recent experience delivering production-grade decision-support or autonomous software systems.
• Master’s degree, PhD, or equivalent industry experience in Computer Science, Artificial Intelligence, Machine Learning, Computational Sciences, or another highly quantitative discipline.
• Demonstrated ability to translate emerging technical concepts, research findings, or novel methodologies into scalable production solutions with measurable business outcomes.
• Strong understanding of modern application architectures involving complex workflows, dynamic decision-making, external system integrations, and context-aware execution.
• Experience designing systems that coordinate multiple services, manage state across interactions, and execute multi-stage processes reliably in production environments.
• Strong analytical mindset with experience establishing evaluation methodologies, performance benchmarks, and data-driven quality measurement frameworks for probabilistic or adaptive systems.
• Ability to critically assess technical literature, evaluate new approaches, and apply them pragmatically within real-world engineering constraints.
• Strong software engineering fundamentals, including Python development, distributed systems, scalability, reliability, and system design.
• Excellent communication skills and ability to collaborate effectively across research, product, and engineering functions.

Nice to have:

• Experience supporting research-intensive, experimentation-driven, or highly analytical workflows.
• Experience providing technical leadership, mentoring engineers, or influencing architectural direction within a team.
• Familiarity with information retrieval, contextual knowledge management, workflow coordination, or advanced automation platforms.
• Exposure to scientific computing, computational research environments, or other data-intensive domains is beneficial.