Senior Product Engineer (AI)

About LJI

Loyalty Juggernaut (LJI) is a leading B2B SaaS company redefining how enterprises drive customer engagement and loyalty. Our flagship platform, GRAVTY®, enables global brands to transform loyalty programs into measurable, revenue-generating growth engines.
Built as an AI-first, next-generation solution, GRAVTY® empowers organizations to deliver highly personalized, real-time experiences at scale—helping them increase customer lifetime value and deepen brand relationships.
Headquartered in Palo Alto, California, LJI partners with leading enterprises across 16 major industries including airlines, retail, hospitality, financial services and telecommunications powering some of the most innovative loyalty ecosystems worldwide.

Our Global Impact:

• 400+ Million members connected through our platform.
• 100+ Global Brands trust us to drive loyalty and brand devotion.
• 3-Time Winner of “Best Technology Innovation in Loyalty”.
• Global recognitions for Excellence in Loyalty Management under numerous categories.
• Recognised as a ‘Strong performer’ in The Forrester Wave™ Loyalty Platforms, Q4 2025.
  
  Explore more about us at www.lji.io

As part of our continued growth, we are expanding our AI Engineering Team to build and scale AI-driven product capabilities that power intelligent engagement across our platform.

We are seeking highly skilled and motivated Senior Product Engineers – AI to join our AI engineering group in Hyderabad.
These roles will focus on developing, deploying, and optimizing machine learning and generative AI solutions that integrate directly into our core product ecosystem.

The ideal candidates are problem-solvers with strong technical depth in Python, data analysis, and machine learning — complemented by excellent communication skills and the ability to collaborate effectively across cross-functional teams.

Key Responsibilities:

• Design, develop, and deploy AI-driven product features using ML, NLP, or GenAI technologies.
• Work closely with product managers, data scientists, and platform engineers to deliver scalable AI solutions.
• Build and maintain end-to-end ML pipelines — from data preparation and model training to deployment and monitoring.
• Analyze data and experiment with techniques to improve model accuracy, performance, and business impact.
• Integrate models into production microservices and APIs.
• Follow best practices in software development, version control, CI/CD, and testing.
• Document solutions, share knowledge, and contribute to technical reviews.
• Stay current with advancements in AI frameworks and modern engineering practices.

Core Requirements

• Problem-Solving: Strong analytical and problem-solving skills; ability to think through complex scenarios and propose effective solutions.
• Programming: Proficiency in Python with experience using data and ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch).
• Machine Learning: Hands-on experience in building, evaluating, and deploying ML models.
• Data Analysis: Strong data manipulation and insight extraction skills using Python and analytical tools.
• Communication: Exceptional written and verbal communication skills — must be able to document, present, and discuss technical topics clearly with both technical and non-technical stakeholders.

You would make a GREAT FIT if you have :

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 3 to 5 years of experience.
• Problem-Solving: Strong analytical and problem-solving skills; ability to think through complex scenarios and propose effective solutions.
• Programming: Proficiency in Python with experience using data and ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch).
• Machine Learning: Hands-on experience in building, evaluating, and deploying ML models.
• Data Analysis: Strong data manipulation and insight extraction skills using Python and analytical tools.
• Communication: Exceptional written and verbal communication skills — must be able to document, present, and discuss technical topics clearly with both technical and non-technical stakeholders.
  

Key Attributes

• Ownership mindset with high accountability.
• Passion for AI innovation and continuous learning.
• Strong collaboration and teamwork orientation.
• Ability to balance technical depth with product-level thinking.