VP of Engineering

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.
The core responsibilities for the job include the following:
Technology and 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 and Platform Management:
Lead platform engineering, product technology, DevOps, infrastructure, and Quality Engineering.
Build robust cloud-native systems using Azure, AWS, and GCP ecosystems.
Oversee operational effectiveness, including uptime, production reliability, and cost optimization.
Innovation and AI Strategy:
Spearhead Mission AI by developing scalable and production-grade AI/ML and GenAI capabilities.
Own the GenAI/LLM Solutions Architecture.
Core specialization in AI Agents and Autonomous workflows, Data Extraction and Intelligent Automation.
Direct hands-on architectural oversight of Large Language Models (LLMs), Applied AI, and multi-layered deep learning products.
Extensive expertise in building intelligent document automation systems (similar complexity to patent parsing, legal workflow automation, and structured decision intelligence tools).
Technical Leadership:
Proven track record overseeing product architecture, tech strategy, and crossfunctional 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.
Future Success indicators:
Mission AI: Build a world-class AI system leveraging GenAI, ML, and enterprise-grade data engineering.
Hyper-Scaling: Architect and scale our platform to match global industry leaders in the IP space.
Culture Building: Develop a strong engineering organization with high ownership, performance, and innovation DNA.
Requirements:
10-15 years of enterprise software engineering experience across B2B SaaS or technology-first companies.
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 comprising 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 modeling, and unstructured data management.
Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).

Experience
10-14 yrs