We are seeking an experienced and visionary Head of Engineering to lead our technical team and drive the development of our cutting-edge SaaS platform. This is a critical leadership role for an individual who is passionate about building innovative B2B/enterprise software, has a deep understanding of modern technology stacks, and possesses hands-on experience in AI and machine learning, particularly with large language models (LLMs). The ideal candidate will have a proven track record of leading and scaling engineering teams in a fast-paced, startup environment.

Key Responsibilities :

- Lead and Mentor : Oversee and guide the entire engineering team, fostering a culture of technical excellence, collaboration, and continuous learning.

- Strategic Direction : Develop and execute the technical roadmap, ensuring alignment with the company's business goals and product vision.

- Architecture and Development : Drive the design and implementation of scalable, reliable, and secure systems, with a focus on modern full-stack development and cloud-native architectures.

- AI/ML Integration : Spearhead the integration of advanced AI and machine learning workflows, including retrieval-augmented generation (RAG) and agent-based AI, into our core products.

- Operational Excellence : Implement best practices in DevOps, data pipelines, and quality assurance to ensure efficient and robust product delivery.

- Recruitment and Growth : Build and scale the engineering team, attracting top talent and supporting their professional growth.

Qualifications and Experience :

- 8 - 12+ years of professional experience in software engineering, systems architecture, or product engineering.

- Proven leadership in building and scaling SaaS platforms or B2B/enterprise software.

- Startup or early-stage growth experience is strongly preferred.

- A solid background in a relevant industry such as fintech, regtech, tax technology, B2B compliance tools, or enterprise data/AI platforms.

- Required experience working with LLMs and agent-based AI.

- Strong technical foundation in modern full-stack development.

- Hands-on experience with cloud infrastructure, particularly AWS/GCP.

- Exposure to AI/ML workflows, including practical experience with concepts like RAG, LangChain, or other LLM-based applications.

- A Bachelors or Masters in Computer Science, Engineering, or a related field.