Vice President — Engineering at Clairvolex
Bengaluru, Karnataka, India · noida · full time · executive level
Compensation: INR 11000000–12000000 per year
About the role
## About Clairvolex Clairvolex offers global patent portfolio development capabilities to enterprises and IP law firms using its proprietary Clair AI platform and Expert Centers. Some of the world's most innovative companies are its clients. Clairvolex raised Series A and Series B investments from Silicon Valley, led by Celesta Capital, and has business operations in the San Francisco Bay Area and in Bengaluru and Gurgaon in India. Its AI products work over legal rules and patent law, document and PDF extraction, and SOPs that can run to 30 pages, against US and European rules that change over time — systems materially more complex than a chatbot, a CRM or basic workflow automation. ## About the role You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem. **Reports to:** CEO · **Location:** Bengaluru, India — hybrid, 3 days a week in office ## What you will do ### Technology & product leadership - Define and drive the technology vision, architecture and long-term platform roadmap. - Oversee the architecture, design and delivery of highly scalable enterprise systems. - Ensure engineering excellence, velocity and reliability across the product lifecycle. ### Engineering & platform management - Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering. - Build robust cloud-native systems using the Azure, AWS and GCP ecosystems. - Oversee operational effectiveness, including uptime, production reliability and cost optimisation. ### Innovation & AI strategy - Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities. - Own the GenAI/LLM solutions architecture. - Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation. - Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products. - Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools. ### Technical leadership - A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms. - Collaborate with executive leadership on business strategy, client requirements and product delivery. - Build, mentor and scale high-performing engineering teams with a growth mindset. - Establish a strong technology culture grounded in ownership, innovation and continuous learning. ## What success looks like - **Mission AI:** build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering. - **Hyper-scaling:** architect and scale the platform to match global industry leaders in the IP space. - **Culture building:** develop a strong engineering organisation with high ownership, performance and innovation DNA. ## Qualifications & experience - Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer. - A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence. - Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up. - Proven leadership in defining and executing technology strategy and platform roadmaps. - Extensive cloud-native engineering experience with Azure, AWS and GCP. ## Technical expertise - Strong full-stack engineering background (Java, Python, JavaScript frameworks). - Expertise with JS frameworks such as React, Angular and Node.js. - Experience building and scaling distributed systems and microservices. - Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management. - Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines). ## Behavioural & leadership competencies - Product and delivery management expertise, end to end, including delivery and customer support. - Excellent communication, with the ability to influence executive stakeholders. - High technical proficiency combined with strong business acumen. - Strong analytical and decision-making skills.
Responsibilities
- Define and drive the technology vision, architecture and long-term platform roadmap.
- Oversee the architecture, design and delivery of highly scalable enterprise systems.
- Ensure engineering excellence, velocity and reliability across the product lifecycle.
- Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
- Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
- Oversee operational effectiveness, including uptime, production reliability and cost optimisation.
- Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
- Own the GenAI/LLM solutions architecture.
- Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
- Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
- Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.
- A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
- Collaborate with executive leadership on business strategy, client requirements and product delivery.
- Build, mentor and scale high-performing engineering teams with a growth mindset.
- Establish a strong technology culture grounded in ownership, innovation and continuous learning.
Requirements
- ## Qualifications & experience - Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer. - A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence. - Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up. - Proven leadership in defining and executing technology strategy and platform roadmaps. - Extensive cloud-native engineering experience with Azure, AWS and GCP.
- ## Technical expertise - Strong full-stack engineering background (Java, Python, JavaScript frameworks). - Expertise with JS frameworks such as React, Angular and Node.js. - Experience building and scaling distributed systems and microservices. - Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management. - Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).
- ## Behavioural & leadership competencies - Product and delivery management expertise, end to end, including delivery and customer support. - Excellent communication, with the ability to influence executive stakeholders. - High technical proficiency combined with strong business acumen. - Strong analytical and decision-making skills.
Skills: Engineering Leadership, GenAI / LLMs, AI Agents, Platform Architecture, Document Intelligence, Multi-agent Orchestration, Distributed Systems, Microservices, Java, Python, React, Node.js, Azure, AWS, GCP, DevOps, Quality Engineering, Technology Strategy, B2B SaaS
Browse more jobs on 100Networks