• Provide technical feasibility and evaluation of the product based on the business needs • Provide technical leadership to the team in design finalization, code reviews, and resolving production support and maintenance issues • Lead design and implementation of critical software components and systems • Mentor technical members of the team • Contribute to the development of coding standards, best practices, and guidelines • Collaborate with stakeholders to define and execute the technical roadmap • Stay informed about emerging technologies and industry trends to drive technical innovation • Hands-on role which involves coding on day-to-day basis • Lead domain modelling designs • Responsible for production on-call duties like any other team member • Produce high quality design documentation

• Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our driving systems. • Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world autonomous driving and robotics applications. • Explore novel data generation and collection strategies to improve diversity and quality of training datasets. • Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met. • Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.

• Build robust, well-designed and effective software that solves complex problems. • Test, review and deploy code quickly. We deploy over 10 times per day and manage major releases with feature flags rather than coordinated deployments. • Research, learn and share new techniques for solving complex engineering problems. We’re a highly collaborative team and we push each other to find better solutions every day. • Write tools and develop practices for the engineering team. From GraphQL-to-Typescript compilers to fully automated deployments, we take the time to invest heavily in our own productivity. • Own projects from end-to-end. On a given day you might be building a system to measure search engine performance, reworking an integration with a telephony provider, or designing a UI component library. • Analyze and design solutions to business problems. Companies that throw solutions over the wall to engineers are wasting half their abilities. At AlphaSense, you’ll be fully involved in determining what to do, not just doing it. • Mentor senior engineers, shape technical culture, and raise expectations for system design and execution. • Contribute to long-term technical strategy while remaining hands-on with critical implementations.

• Maintain and improve the internal flows, services, and modules that enable the AI agent to operate stably and efficiently. • Implement technical optimizations aimed at improving performance, resource usage, and response times. • Diagnose, resolve, and prevent agent-related incidents, including root cause analysis and hardening actions. • Develop test agents, experimentation environments, and A/B variants that enable continuous technical iteration. • Perform technical prompt engineering adjustments (context, parameters, configurations) necessary for the agent's operation.