Manoj Desai

VP of Engineering

Bengaluru, Karnataka, India11 yrs 6 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in building enterprise AI platforms at scale.
Pioneered generative AI applications for marketing innovation.
Led cross-functional teams to drive AI transformation.

Stackforce AI infers this person is a SaaS and Fintech expert specializing in AI-driven solutions and data science.

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Skills

Core Skills

Artificial Intelligence (ai)Cloud ApplicationsTeam LeadershipData ScienceMachine LearningStatistical Modeling

Other Skills

Enterprise AI Platform StrategyProduction-Grade Agentic AIMulti-Model AI ArchitectureEnterprise AI Integration LayerScalable AI InfrastructureAI Platform EnablementProduct LeadershipTeam ManagementBusiness ImpactAI platform developmentCross-functional initiativesData AnalysisMultimodal UnderstandingGenerative AI applicationsMarketing innovation

About

Generative AI | Data Science | Quant Trading

Experience

11 yrs 6 mos

Total Experience

2 yrs 9 mos

Average Tenure

6 mos

Current Experience

Albertsons companies india

Senior Engineering Manager

Dec 2025 – Present · 6 mos

Leading the strategy, architecture, and execution of enterprise AI platforms that enable production-grade Agentic AI at scale across the organization.
Responsible for building the foundational AI platform ecosystem that allows engineering and business teams to design, deploy, and operate intelligent agents integrated with enterprise systems, data platforms, and operational workflows.
Driving the transition from isolated AI initiatives to a platform-led AI operating model, enabling secure, governed, and scalable adoption of generative and agentic AI across thousands of users and multiple business domains.
Key responsibilities include:
Enterprise AI Platform Strategy – Defining the long-term architecture and operating model for large-scale AI adoption across the enterprise.
Production-Grade Agentic AI – Enabling the design, orchestration, and lifecycle management of autonomous AI agents operating within real business workflows.
Multi-Model AI Architecture – Architecting flexible platforms that orchestrate multiple frontier models while optimizing for reliability, performance, and cost.
Enterprise AI Integration Layer – Enabling agents to interact with enterprise collaboration tools, data platforms, and operational systems.
Scalable AI Infrastructure – Establishing cloud-native, identity-aware AI infrastructure with enterprise-grade governance, security, and compliance.
AI Platform Enablement – Empowering engineering teams and domain experts to build and deploy AI-driven automation through reusable platform capabilities.
Focused on building AI as a core enterprise capability, transforming how teams automate processes, access knowledge, and operate intelligent systems at scale.

Enterprise AI Platform StrategyProduction-Grade Agentic AIMulti-Model AI ArchitectureEnterprise AI Integration LayerScalable AI InfrastructureAI Platform Enablement+2

Rakuten

5 roles

Senior Manager - AI Products

Promoted

Aug 2025 – Dec 2025 · 4 mos

Leading Rakuten's AI product portfolio and driving enterprise-wide AI transformation
In this role, I'm responsible for:
Product Leadership: Overseeing multiple enterprise AI products serving 40,000+ employees, developers, and B2B customers across Rakuten's global ecosystem
Team Management: Leading a diverse team of AI researchers, backend & frontend engineers, QA specialists, and infrastructure experts across India & Japan
Business Impact: Driving initiatives with an estimated cumulative impact of ¥2 Billion
My focus is on scaling AI solutions that deliver measurable business value while maintaining the highest standards of quality and innovation.

Product LeadershipTeam ManagementBusiness ImpactArtificial Intelligence (AI)Team Leadership

Manager - Data Science

Apr 2024 – Aug 2025 · 1 yr 4 mos

Built and launched Rakuten AI for Rakutenians - our flagship enterprise AI platform
Key Achievements:
Delivered a comprehensive AI platform featuring RAG, web search, deep research, data analysis, and multimodal understanding (image & audio)
Scaled the platform to 40,000 employees
Led cross-functional initiatives aligning AI roadmap with corporate strategy

AI platform developmentCross-functional initiativesArtificial Intelligence (AI)Data Science

Lead Data Scientist

Jun 2022 – Apr 2024 · 1 yr 10 mos

Pioneered generative AI applications at Rakuten, driving marketing innovation and customer engagement
Major Projects:
AI Banner Studio - Creative automation platform
Built a generative AI platform leveraging advanced language models and image generation APIs
Enabled automated creation of high-converting ad campaigns based on user personas and behavioral data
Interest Pool Segmentation Engine
Developed ML models for Rakuten mobile to identify high-propensity user segments
Increased conversion rates by 13% and subscription adoption by 18%
Implemented cohort analysis and propensity modeling at scale

Generative AI applicationsMarketing innovationCustomer engagementArtificial Intelligence (AI)Data Science

Senior Data Scientist II

Promoted

Jun 2021 – Jun 2022 · 1 yr

Empowered Rakuten merchants with data-driven insights for growth
Key Project: RFM-based Marketing Intelligence Tool
Designed a sophisticated recommendation system for Rakuten's merchant ecosystem
Enabled data-driven shop discovery, competitive benchmarking, and dynamic pricing optimization
Used RFM analysis combined with collaborative filtering to identify similar merchant profiles

Data-driven insightsRecommendation systemsData ScienceMachine Learning

Data Scientist

May 2020 – Jun 2021 · 1 yr 1 mo

Foundation for data-driven decision making at Rakuten
Major Initiatives:
Rapid Query
Built a federated query engine using PySpark, Presto, and Apache Hive
Democratized availability of data access for 500+ analysts and researchers across the organization
Reduced average query response time by 73%, processing 5+ million queries annually
Brand Gateway Impact Analysis
Conducted comprehensive digital channel attribution using causal inference methodologies
Implemented Markov chain attribution models and Shapley value analysis

Data-driven decision makingFederated query engineData ScienceMachine Learning

Wealthengine

Data Scientist

Jun 2019 – May 2020 · 11 mos

Scaled machine learning solutions and built wealth intelligence systems for 250M+ individuals
Key Achievements:
AutoML Platform
Architected an enterprise-grade AutoML platform on AWS (EC2, S3, Lambda, SageMaker)
Built ensemble learning pipelines featuring Random Forest, XGBoost, LightGBM, and Gradient Boosting
Delivered ML-as-a-Service capabilities for enterprise clients, creating new revenue streams
Enabled non-technical teams to build and deploy production-grade ML models
WealthScore - Proprietary Wealth Assessment System
Developed a revolutionary wealth prediction model using deep neural networks and clustering algorithms
Evaluated financial strength of 250 million U.S. individuals at unprecedented scale
Combined multiple data sources and advanced ML techniques to create actionable wealth intelligence

Machine learning solutionsWealth intelligence systemsMachine LearningData Science

Centillion research

Data Scientist

Dec 2017 – May 2019 · 1 yr 5 mos · Bengaluru Area, India

Built quantitative trading models and owned the complete ML lifecycle for live financial markets
Key Responsibilities:
Algorithmic Trading Model Development
Enhanced trading model performance through stepwise linear regression with forward feature selection
Developed multivariate Gaussian anomaly detection frameworks ensuring robust data quality
Reduced false trading signals by 42%, significantly improving model reliability
Applied advanced statistical techniques to optimize risk-adjusted returns
Live Trading Operations
Took full ownership of model development lifecycle for Index-options and stock-options trading
Managed live trading operations with real capital at stake
Generated comprehensive performance reports and continuously refined strategies
Achieved Sharpe ratio of 2.1 - demonstrating strong risk-adjusted performance

Quantitative trading modelsMachine learning lifecycleData ScienceMachine Learning

Robert bosch engineering and business solutions ltd

Machine Learning Engineer

Oct 2014 – Nov 2017 · 3 yrs 1 mo · Bangalore

Sensor Inference & Predictive Maintenance
Developed Artificial Neural Network-based systems for automotive sensor arrays
Conducted research proving sensor correlation hypothesis for fault-tolerant infrastructure
Achieved 94% accuracy in sensor failure prediction, enabling proactive maintenance
Built ML models that could infer missing sensor data from correlated sensors
Contributed to next-generation automotive safety and reliability systems
Automated Test Classification System
Implemented Decision Tree algorithms (CART, Random Forest) for software validation
Optimized testing processes for embedded automotive products
Improved testing efficiency by 38% while enhancing quality assurance protocols
Reduced manual effort in test case classification and execution