Vice President of Engineering

About the Role
We are looking for a highly hands-on VP – Engineering with deep expertise in Data Engineering and Artificial Intelligence to lead our engineering organization. You will own the complete journey from understanding customer requirements to architecting, building, deploying, and successfully delivering data- and AI-driven products.
This is not a purely managerial role. We want a strong technology leader who sets strategy and builds high-performing teams, and who is equally capable of stepping into complex technical challenges whenever required.
What You Will Do
Own the end-to-end product engineering lifecycle: requirement discovery, architecture, development, testing, deployment, and production support
Define and drive the data and AI technology roadmap, including platform architecture, data strategy, and ML/GenAI adoption
Lead Engineering, Data Engineering, ML/AI, QA, DevOps, Product, and Customer teams toward high-quality, timely delivery
Review code and architecture, debug complex issues, and resolve critical technical problems hands-on
Work directly with customers to understand business needs, translate them into scalable data and AI solutions, and confidently recommend the right approach
Establish engineering best practices across release management, data quality, observability, performance optimization, and production reliability
Drive AI adoption across the software development lifecycle to boost productivity, accelerate delivery, improve code quality, and automate repetitive work
What We Are Looking For
Core Engineering
Strong hands-on expertise in Java, Python, JavaScript, Microservices, REST APIs, server-side development, and system architecture
Proven experience designing scalable, high-performance, production-grade product architectures
Data Engineering
Deep experience building and scaling data platforms: batch and real-time pipelines, ETL/ELT, data lakes, lakehouses, and data warehouses
Hands-on knowledge of tools such as Apache Spark, Kafka, Airflow, dbt, Flink, Snowflake, Databricks, BigQuery, or Redshift
Strong understanding of data modeling, data governance, data quality, lineage, security, and compliance
Experience with both SQL and NoSQL data stores and with optimizing data workloads for performance and cost
Artificial Intelligence & Machine Learning
Strong understanding of the ML lifecycle: feature engineering, model training, evaluation, deployment, monitoring, and MLOps
Practical experience with Generative AI and LLMs, including RAG architectures, vector databases, prompt engineering, fine-tuning, agents, and evaluation frameworks
Familiarity with frameworks and platforms such as TensorFlow, PyTorch, Hugging Face, LangChain, MLflow, and cloud AI services (SageMaker, Azure ML, Vertex AI)
Ability to responsibly productionize AI, with attention to cost, latency, scalability, security, and governance
Cloud, DevOps & Delivery
Strong understanding of AWS, Azure, or GCP, along with CI/CD, Git, Docker, Kubernetes, and Infrastructure as Code
Solid grasp of QA and test automation, release management, production support, observability, and performance optimization
Experience with DataOps and MLOps practices
Leadership & Customer Engagement
Strong leadership and ownership, with a track record of building and scaling engineering teams, including data and AI specialists
Excellent communication skills, with the ability to engage CXOs and technical stakeholders and to explain complex data and AI concepts clearly
Ability to balance strategic thinking with hands-on execution
AI Across the SDLC
AI expertise is critical for this role. We are looking for someone who understands how to leverage AI effectively across the software development lifecycle to:
Enhance engineering productivity with AI-assisted coding, code review, and documentation
Accelerate development and testing through automation
Improve code quality, test coverage, and defect detection
Automate repetitive engineering, DevOps, and data operations tasks
Improve overall product delivery speed and reliability
Ideal Candidate Profile
The ideal candidate may not code every day, but brings deep technical and hands-on expertise and the confidence to dive into complex technical problems whenever required. You enjoy building data- and AI-powered products, solving complex problems, and owning outcomes from idea to production.

Work arrangement
Yes