We are looking for a highly skilled and experienced Principal Software Engineer to lead our engineering team and drive the development of robust, scalable, and high-performance software applications - including AI-powered products built on modern LLM and ML systems. In this role, the candidate will be responsible for overseeing the entire software development lifecycle, from design and development to deployment and maintenance, while establishing the practices and standards for how the team builds with AI. The candidate will work closely with cross-functional teams, including product managers, designers, and other engineers, to deliver innovative solutions that meet our business objectives.

Responsibilities:
• Lead the design, development, and deployment of full-stack software applications.
• Architect and implement scalable, secure, and high-performance solutions.
• Architect and integrate AI/ML capabilities into core products - including LLM-powered features, retrieval-augmented generation (RAG), and agentic workflows - with attention to latency, cost, evaluation, and reliability.
• Establish and lead a disciplined, spec-driven approach to AI-assisted software engineering: clear specifications, design intent, and acceptance criteria that drive AI tooling, with rigorous review, testing, and validation - explicitly not ad-hoc "vibe coding."
• Define team standards for building with AI, including prompt and context engineering, model evaluation and guardrails, and responsible-AI considerations (safety, bias, data privacy).
• Drive adoption of AI coding assistants and agentic development tools to raise velocity and code quality, while maintaining engineering rigor and accountability for what ships.
• Mentor and guide junior and mid-level engineers, fostering a culture of continuous learning and improvement.
• Collaborate with product managers, designers, and other stakeholders to define project requirements and specifications.
• Ensure code quality and maintainability through code reviews, testing, and best practices.
• Optimize application performance and troubleshoot issues across the stack.
• Stay up-to-date with emerging technologies and industry trends, and apply them to improve our development processes and products.
• Contribute to strategic planning and decision-making as a key member of the engineering leadership team.

Requirements:
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 10+ years of professional experience in full-stack development, with a strong emphasis on both frontend and backend technologies.
• Hands-on experience designing and shipping production features built on large language models or other ML systems - including integration, evaluation, guardrails, and monitoring - using the modern AI/LLM stack: model APIs (OpenAI, Anthropic, or similar), orchestration frameworks (LangChain, LlamaIndex or similar), and vector databases.• Demonstrated experience leading AI-assisted, spec-driven engineering: defining specifications and acceptance criteria that guide AI tooling, with strong review and testing discipline rather than unstructured generation.
• Strong proficiency in backend technologies such as Node.js, Python, Ruby, Java, Golang, or similar.
• Expertise in frontend technologies such as HTML, CSS, JavaScript, and modern frameworks like React, Angular, or Vue.js.
• Experience with database design and management, including SQL and NoSQL databases.
• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Expertise in distributed computing, networking, microservices, and serverless architecture.
• Solid understanding of DevSecOps practices and CI/CD pipelines.
• Excellent problem-solving skills and the ability to think critically and strategically.
• Strong leadership and communication skills, with the ability to mentor and inspire team members.
• Proven track record of delivering high-quality software on time and within budget.
• Knowledge of security best practices and compliance standards.

Preferred Qualifications:
• Familiarity with MLOps and the lifecycle of deploying, versioning, and monitoring models in production.
• Good understanding of Data Engineering, Business Intelligence, and Big Data Analytics.
• Prior experience in a leadership or management role.
• Contributions to open-source projects or a strong personal portfolio.