Principal Software Engineer

Job Description

Architect Develop Core Systems: Lead the design and implementation of scalable, secure, and highly available enterprise cloud AI platform services and infrastructure. Drive the evolution of our microservices architecture to improve performance, resilience, and developer productivity. Technical Leadership Mentorship: Provide technical guidance and mentorship to engineers fostering a culture of continuous improvement and learning. Establish and enforce best practices, and development methodologies to ensure quality and maintainability of cutting-edge AI systems and solutions Cross-Functional Collaboration: Partner with other AI research and engineering teams, product and UX teams to translate business needs into efficient, reliable, and user-centric software solutions. Lead architectural reviews and contribute to roadmap planning, ensuring alignment with company goals and strategic initiatives. AI Innovation Exploration: Evaluate current and emerging AI technologies, frameworks, and tools to drive innovation and efficiency within the engineering organization. Experiment with and implement advanced AI/ML methods in collaboration with the AI research engineering team and help shape the technical strategy for the enterprise AI platform Quality, Security, Compliance: Advocate for best-in-class CI/CD, automated testing, observability, and security practices, leveraging AI Ensure compliance with industry standards, data privacy laws, and internal security policies. Qualifications Educational Background: Bachelor s or masters degree in Computer science, ML/AI, Software Engineering, or related field. Equivalent experience also considered. Technical Expertise: 12+ years of software development experience, with at least 3 years in a lead or principal engineering role. Proven track record building distributed, high-volume, low-latency systems using modern programming languages (e.g., Python, Go, Java, or C++). Strong understanding of cloud-native architectures, containers, and orchestration systems (e.g., Kubernetes) and familiarity with AWS, GCP, or Azure. Experience with SQL/NoSQL databases, streaming platforms (e.g., Kafka), and scalable storage solutions. Deep knowledge of microservices, RESTful APIs, GraphQL, and event-driven design patterns. AI/ML Data Skills: Deep expertise and experience building and leveraging machine learning workflows and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) in a platform to drive business critical products and solutions. Expertise and experience building platforms and applications with modern GenAI technologies, LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. in production environments. Soft Skills Leadership: Exceptional communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders both within and outside the company. Strong problem-solving skills, attention to detail, and ability to drive projects from concept to completion. Demonstrated ability to lead and influence without direct authority, working effectively in a collaborative, fast-paced startup environment.