AI Engineer

DropXcell; Kerala; On-site; INR 7,800,000 - 13,001,000; Full time

Job summary

Finanshels is seeking an AI Engineer to design, deploy scalable ML models and robust ETL/ELT pipelines that transform high-volume financial data into production-ready intelligent systems. You’ll own data ingestion, model development, deployment, and monitoring in production.

You’ll collaborate with data engineers, product managers, and finance domain experts to translate business needs into AI solutions, while upholding security and compliance in a regulated environment.

Qualifications

• 8+ years of experience in software/data engineering with emphasis on ML

Responsibilities

• Design, build, and deploy scalable ML models for financial automation

Skills

Machine learning

Data engineering

Python

SQL

ETL/ELT pipelines

MLops

Cloud platforms

Model deployment

Problem solving

Communication

Tools

TensorFlow

PyTorch

scikit-learn

Airflow

dbt

Spark

Kafka

Job description

Finanshels.com is the UAE's leading tech-enabled accounting and tax platform, trusted by thousands of startups and SMBs across the MENA region. We combine automation, real-time financial insights, and expert finance professionals to help founders manage bookkeeping, VAT, corporate tax, and compliance on a single platform. As we scale, we're investing heavily in AI to make financial operations smarter, faster, and more predictive - and we're looking for an AI Engineer to help build the intelligent systems that power that vision.

About the Role

We're looking for an experienced AI Engineer to sit at the intersection of machine learning and data engineering. You'll design and deploy scalable ML models and build the robust ETL/ELT pipelines that feed them — turning messy, high-volume financial data into production-ready intelligent systems that our finance teams and customers rely on every day.

This is a hands-on, end-to-end role: you'll own everything from data ingestion and pipeline architecture to model development, deployment, and monitoring in production.

What You'll Do

• Design, build, and deploy scalable machine learning models to support financial automation, forecasting, anomaly detection, and other intelligent product features.
• Architect and maintain robust ETL/ELT data pipelines that reliably move and transform data from diverse financial and operational sources.
• Own the full ML lifecycle — from data collection and feature engineering to model training, validation, deployment, and ongoing monitoring in production.
• Collaborate closely with data engineers, product managers, and finance domain experts to translate business problems into AI-driven solutions.
• Build and maintain infrastructure for model serving, versioning, and CI/CD to ensure reliable, scalable deployment of AI systems.
• Monitor deployed models for performance, drift, and data quality issues, and iterate to keep systems accurate and reliable at scale.
• Ensure data pipelines and ML systems meet standards for security, compliance, and data privacy appropriate to a regulated financial environment.
• Evaluate and integrate relevant AI/ML tools, frameworks, and third-party APIs (including LLMs) to accelerate development where appropriate.
• Document architecture, models, and pipelines to support knowledge sharing and long-term maintainability.
• Mentor junior engineers and contribute to best practices for AI/ML development within the engineering team.

What We're Looking For

• ~8 years of overall experience in software/data engineering, with substantial hands-on experience in machine learning and AI system design.
• Proven experience designing, training, and deploying machine learning models in production environments at scale.
• Strong experience building ETL/ELT data pipelines using modern data engineering tools and practices.
• Solid programming skills in Python (and familiarity with SQL); experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with data pipeline/orchestration tools (e.g., Airflow, dbt, Spark, Kafka, or similar).
• Familiarity with cloud platforms (AWS, GCP, or Azure) and cloud-native data/ML services.
• Experience with MLOps practices — model versioning, CI/CD for ML, monitoring, and reproducibility.
• Understanding of data warehousing concepts and experience working with large-scale structured and unstructured data.
• Strong analytical and problem-solving skills, with the ability to translate ambiguous business needs into technical solutions.
• Excellent communication skills and the ability to work cross-functionally with engineering, product, and finance teams.

Nice to Have

• Experience applying AI/ML in fintech, accounting, or financial services.
• Hands-on experience with large language models (LLMs), RAG pipelines, or generative AI applications.
• Experience with real-time data processing and streaming architectures.
• Familiarity with data governance, security, and compliance requirements in regulated industries.

Why Join Finanshels

• Be part of a fast-growing fintech reshaping how startups and SMBs across the MENA region manage their finances.
• Work on high-impact AI systems with direct exposure to real financial data and business outcomes.
• Collaborative, founder-led culture that values ownership, speed, and continuous learning.
Competitive compensation and the opportunity to shape the AI strategy of a scaling company from an early stage.