Santhosh Kumar M.

Co-Founder

Hyderabad, Telangana, India21 yrs 3 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Co-founder of an innovative AI startup.
Expert in AI architecture and strategy.
Proven track record in data engineering leadership.

Stackforce AI infers this person is a Fintech and AI solutions architect with extensive experience in enterprise-level data engineering.

Contact

santhoshmallojwala@gmail.com LinkedIn

Skills

Core Skills

Artificial Intelligence (ai)Product StrategyGenerative AiTechnical ArchitectureMachine LearningData EngineeringBusiness InsightsData Management

Other Skills

Agile Application DevelopmentAgile MethodologiesAgile Project ManagementAmazon Web Services (AWS)Analytical SolutionsAnalyticsApache KafkaApache SparkApache Spark MLApache Spark StreamingApache StormApplied ElectronicsArchitectural DesignAzure Data FactoryAzure Data Lake

About

Co-founder of a stealth-mode AI startup focused on building advanced platforms that leverage LLMs, agentic AI, and neuro-symbolic reasoning to transform enterprise decision-making. We aim to solve high-impact challenges across financial services, compliance, and manufacturing. I lead the overall strategy—spanning product vision, AI architecture, and go-to-market—combining deep research with scalable engineering to deliver intelligent, autonomous systems that drive real business value. With nearly two decades of leadership experience in Software Development, Data Engineering, and Artificial Intelligence, I bring deep technical and strategic expertise in Java, Python, Spark, Databricks, and Azure Cloud. Previously, I held leadership roles at Mashreq, DBS, Franklin Templeton, GE Digital, and Persistent Systems, where I led large-scale Data & AI transformation initiatives across banking, investment, and industrial domains. I was responsible for defining enterprise strategies, architecting end-to-end solutions, and establishing governance frameworks that ensured scalability, compliance, and measurable impact. Across these roles, I specialize in translating complex business challenges into innovative Data & AI solutions, driving adoption of advanced analytics, and championing best practices in AI Engineering, MLOps, and Ethical AI practices within highly regulated and data-intensive environments.

Experience

21 yrs 3 mos

Total Experience

2 yrs 10 mos

Average Tenure

1 yr

Current Experience

Point9

Co-Founder | AI Startup

Jun 2025 – Present · 1 yr · Hyderabad, Telangana, India · Remote

Pioneering the development of next-generation AI-driven platforms and products that aim to redefine how modern enterprises and institutions operate.
We’re building a next-gen platform that empowers organizations to operationalize AI responsibly — from intelligent workflows to governance, risk, and compliance automation.
Spearheading product strategy, AI architecture, and go-to-market initiatives.
Building a world-class team passionate about making enterprise AI trustworthy, scalable, and impactful.
Transforming complex enterprise processes into intelligent, compliant, and autonomous systems

Artificial Intelligence (AI)Generative AIPython (Programming Language)Product StrategyTechnical Solution DesignEnterprise Architecture

Mashreq

Head of AI Engineering - AVP

Jul 2024 – Jun 2025 · 11 mos · India · Remote

Responsibilities as AI CoE & AI Architect:
Defined and executed AI/GenAI strategy and roadmap, establishing an AI Center of Excellence (CoE) for governance, adoption, and enterprise-wide enablement.
Designed end-to-end AI architectures including LLMOps, RAG, multi-agent systems, and multimodal AI, integrating with enterprise apps via APIs and microservices.
Delivered LLM-based solutions (GPT, LLaMA, Claude, Mistral) with fine-tuning, prompt orchestration, LoRA/QLoRA, and hallucination mitigation.
Built data & knowledge engineering foundations with vector DBs, embeddings, feature stores, knowledge graphs, and synthetic data pipelines.
Implemented Responsible AI frameworks (ethics, compliance, fairness, explainability) with monitoring, retraining, and adversarial testing.
Architected cloud-native AI infrastructure Azure, Kubernetes, GPU clusters, Spark) for scalable deployments.
Acted as AI evangelist, partnering with CxOs to identify use cases, measure ROI, and drive AI adoption across domains (finance & banking).

Generative AIArtificial Intelligence (AI)Microsoft AzureMicrosoft Azure Machine LearningTechnical ArchitectureTechnical Solution Design

Freelance | ai services

AI Solution Engineer

Apr 2024 – Jul 2024 · 3 mos · Hyderabad, Telangana, India · Remote

Worked as an independent AI Solution Engineer, developing, integrating, and deploying advanced AI/ML and GenAI models across projects in Manufacturing, Private Equity, and Transportation domains. Delivered end-to-end solutions, from prototyping to deployment, leveraging both traditional ML and state-of-the-art deep learning and GenAI frameworks.
🔹 Key Responsibilities:
AI/ML Model Development: Designed and trained predictive and classification models using XGBoost, CatBoost, Lasso Regression, Random Forest, and advanced deep learning architectures (CNN, RNN, BERT, TensorFlow, PyTorch).
Generative AI Integration: Experimented with OpenAI GPT models, GitHub Copilot, LangChain, LlamaIndex, and prompt engineering to integrate GenAI into decision-support and automation workflows.
End-to-End Deployment: Built pipelines for data preprocessing, model training, validation, and deployment on cloud-based environments with scalability in mind.
Cross-Domain Applications:
Manufacturing: Implemented predictive maintenance and defect detection models using CNNs and time-series RNNs, reducing downtime.
Private Equity: Developed risk and performance prediction models using Lasso Regression, XGBoost, CatBoost, supporting investment analysis.
Transportation: Built demand forecasting and route optimization models leveraging Random Forest, RNNs, and BERT-based NLP for logistics documentation.
MLOps & Integration: Applied containerization (Docker), version control (Git), and model serving APIs for seamless deployment into client workflows.
Collaboration & Productivity: Used Copilot for code acceleration, OpenAI GPT APIs for prototyping, and LangChain-based pipelines for LLM-powered document analysis and report generation.
🔹 Technologies & Tools:
Python, TensorFlow, PyTorch, XGBoost, CatBoost, Random Forest, Lasso Regression, BERT, CNN, RNN, Scikit-learn, Pandas, OpenAI APIs, LangChain, Copilot, Docker, FastAPI, REST APIs, Cloud (AWS/Microsoft Azure) AI Services, MLOps workflows.