Staff Software Engineer - Gen AI

Why Join Truva Truva stands at the forefront of SaaS innovation, specializing in automating tasks, optimizing workflows, and delivering unparalleled sales productivity with LLMs. Truva is led by Gaurav - 2x founder and an alumnus of Stanford, and Anuja - an alumnus of Haas MBA from UC Berkeley. Together, they bring a combined experience of 20 years ranging from founding Forbes Top AI 50 startup to lead tech teams at FAANG companies, where they have been instrumental in developing applied ML solutions and infrastructure. Joining Truva.ai means being part of a cutting-edge team committed to driving transformative change in the tech world. About The Role We are actively seeking a Staff Software Engineer with 8 years of experience to spearhead backend development initiatives, optimize system performance, and drive the scale of our solutions. In this role, you will collaborate closely with our founders and an elite team comprising Forbes 30 under 30 serial entrepreneurs, Stanford engineers, and Berkeley MBA graduates, each boasting over 10 years of experience in leading tech giants and innovative startups. As a Staff Software Engineer at Truva.ai, you will be more than just a contributor; you'll act as an advocate and coach for your team. Your day-to-day responsibilities will include solving complex backend challenges, engaging in hands-on coding, and leveraging your leadership skills to enhance product success in our fast-paced startup environment. You'll play a crucial role in building and mentoring the engineering team, ensuring the delivery of high-quality software solutions that meet our ambitious goals. What You'll Do Architect and Design Complex Systems : You'll be responsible for architecting and designing complex systems, scaling them effectively, and experimenting with different technologies to identify the best solutions while maintaining development speed. Product Feature Involvement : Actively participate in product feature decisions, determining the best architecture aligned with business priorities, managing short-term deadlines, and planning for long-term development and scaling. Collaborative Visioning : Engage actively in shaping and refining our technical vision, ensuring alignment with overall company goals and strategies. Process and Productivity Improvement : Continuously seek out and implement improvements in our engineering processes, tools, and systems, enhancing the scalability of our codebase, productivity of our team, and overall efficiency. Talent Acquisition and Development : Play a pivotal role in recruiting and interviewing new team members, crafting interview questions that reflect our values, and nurturing a culture of excellence, velocity, and humility. Mentorship : Inspire and mentor less experienced engineers and interns, fostering a learning environment that encourages growth and innovation. What You'll Need Relevant Experience : A minimum of 8 years of relevant work experience, with a preference for candidates who have demonstrated the ability to ship high-quality Machine Learning based products and features at scale. Engineering Solution Skills : An ability to turn business and product ideas into engineering solutions, showcasing a strong sense of ownership and project leadership from inception to production scaling. Growth Mindset : A desire to work in a fast-paced environment, with a continuous drive to grow, master your craft, and contribute to a team that values excellence, speed, and innovation. Language Skills: Excellent English communication skills, both written and verbal. Product-Focused Mindset: A positive, solution-focused approach towards innovative product development. Advanced Python Expertise : Extended experience with Python, particularly in building highly scalable solutions, is highly valued. Your ability to leverage Python to solve complex problems and scale systems efficiently will set you apart. Bonus Points Machine Learning Application Development : Experience in developing machine learning applications. LLM Expertise : Experience with Large Language Models (LLMs).