AI Data Engineering Lead

Job Title: AI Data Engineering Lead

We're looking for an exceptional AI & Data Engineering Lead to join our India team and accelerate the next generation of intelligent automation across our platform. This is a senior leadership role critical to our growth trajectory and evolution as a company.

You'll architect and implement AI/ML solutions that process millions of transactions, detect anomalies, and extract actionable insights from the massive volumes of invoices, claims, receipts, and assets flowing through our system. This work directly impacts our ability to serve clients better, move faster, and build the sustainable competitive advantages we need in this next chapter.

What You’ll Do

Lead AI/ML Strategy & Execution

• Design and architect end-to-end AI/ML solutions for invoice processing, claims validation, asset categorization, and fraud detection.
• Build, train, validate, and deploy production ML models for OCR, NLP, and anomaly detection at scale.
• Define technical roadmap balancing innovation with speed to market and business value.
• Move quickly from experimentation to production, delivering client value iteratively.
  
  

Build Scalable Data Infrastructure

• Design and build robust data pipelines to ingest, normalize, and process diverse data sources (invoices, claims, receipts, marketing assets).
• Develop ETL/ELT workflows transforming raw, unstructured data into clean, structured datasets.
• Implement data quality checks, validation rules, and monitoring to ensure data integrity.
• Optimize for high-volume processing while maintaining accuracy and reliability.
  
  

Innovate & Adopt

• Stay current with AI/ML advances and identify opportunities to apply new techniques.
• Experiment with emerging technologies to improve accuracy, efficiency, and user experience.
• Adapt quickly as business needs evolve - resilience through uncertainty is part of our DNA.
• Contribute to technical discussions and continuous improvement of our processes.
  
  

Knowledge, Skills, And Abilities

• 8-12 years of experience in data engineering, ML engineering, or AI/ML solution development.
• 3+ years building and deploying production machine learning models.
• Experience with experimentation frameworks (A/B testing, model evaluation pipelines).
• Deep expertise in at least two domains: Computer Vision/OCR, NLP, or Anomaly Detection.
• Strong Python proficiency with ML libraries (scikit-learn, TensorFlow, PyTorch, Keras).
• Experience with MLOps frameworks (MLflow, Kubeflow, or SageMaker).
• Extensive experience building data pipelines (Airflow, Spark, Kafka or similar).
• Strong SQL and experience with relational and NoSQL databases.
• Cloud platform experience (AWS, Azure, or GCP) and ML services.
• Strong grounding in data privacy, security, and compliance for sensitive financial data.
• Proven ability to lead complex projects from conception to deployment.
• Excellent communication and collaboration skills across technical and non-technical stakeholders.