Director of Engineering - Hyper-automation Platform

Role & responsibilities:

Technical Leadership & Strategy

• AI-Driven Development Lifecycle

  : Define, implement, and manage end-to-end AI-powered development processes from initial concept through automated code generation, intelligent change management, seamless deployment, and ongoing support

• Technology Stack Oversight

  : Lead architectural decisions across diverse technology environments while leveraging deep expertise in Java and Python ecosystems

• Large-Scale Product Delivery

  : Orchestrate DevOps practices and methodologies to manage sophisticated product development involving 2+ million lines of code

• Innovation Leadership

  : Drive adoption of generative AI technologies and predictive models to accelerate development velocity and enhance product capabilities

Team Management & Development

• Lead and mentor a high-performing engineering organization of 15-25 engineers across multiple disciplines
• Establish technical vision and roadmap alignment with business objectives
• Foster a culture of continuous learning, experimentation, and technical excellence
• Collaborate with cross-functional teams including Product, Data Science, and Operations

Operational Excellence

• Implement robust CI/CD pipelines and automated testing frameworks for complex, multi-service architectures
• Establish metrics-driven engineering practices with focus on quality, reliability, and performance
• Drive technical debt reduction and system scalability initiatives
• Ensure compliance with security, regulatory, and enterprise governance requirements

Preferred candidate profile:

Technical Expertise

• Programming Proficiency

  : 8+ years of hands-on development experience with strong background in

  Java

   and

  Python

  , plus working knowledge of additional technology stacks (JavaScript/Node.js, Go, C#, etc.)

• AI/ML Experience

  : Demonstrated experience with traditional AI/ML frameworks (scikit-learn, TensorFlow, PyTorch) and

  hands-on implementation

   of predictive analytics, classification, and regression models

• Generative AI Understanding

  : Solid comprehension of Large Language Models (LLMs), prompt engineering, fine-tuning, and integration of generative AI capabilities into enterprise applications

• DevOps Mastery

  : Comprehensive experience with containerization (Docker, Kubernetes), cloud platforms (AWS/Azure/GCP), infrastructure as code, and managing deployments for large-scale applications

Leadership & Management

• Overall 20 years of software industry experience with at least 5+ years in engineering leadership roles with direct team management experience
• Proven track record of delivering complex software products from conception to market
• Experience managing technical teams through high-growth phases and organizational scaling
• Strong communication skills with ability to translate technical concepts to business stakeholders

Domain Knowledge

• Deep understanding of automation technologies, workflow orchestration, and enterprise integration patterns
• Experience with microservices architecture, API design, and distributed systems
• Knowledge of data engineering, ETL processes, and real-time data processing

Preferred Qualifications

• Advanced degree in Computer Science, Engineering, or related technical field
• Experience with HyperAutomation platforms (UiPath, Automation Anywhere, Blue Prism) or RPA technologies
• Background in machine learning operations (MLOps) and model lifecycle management
• Previous experience in startups or high-growth technology companies
• Contributions to open-source projects or technical publications
• Experience with regulatory compliance in enterprise environments (SOC2, ISO 27001, etc.)