From bits to intelligence

Enterprise AI Architect building production-ready AI systems.

I am Sujit Sahoo — a GenAi, ML, MLOps, and data platform leader with 18+ years of experience turning complex enterprise problems into production-grade AI systems, scalable data platforms, and measurable business outcomes.

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Measurable Impact

Proof of execution

A career pattern of making AI, data, and engineering programs production-ready and business-relevant.

18+

Years building enterprise technology and AI systems

25x

Platform performance improvement through modernization

75%

ML productionization rate through standardized MLOps

10

Filed patents, including 6 granted innovation patents

Expertise

Where I create enterprise value

Enterprise AI Architecture

Architect large-scale AI/ML solutions across enterprise ecosystems, aligning business goals, platform design, governance, and measurable outcomes.

MLOps & Production AI

Build CI/CD and CT-enabled ML delivery frameworks that reduce deployment cycles and move experimentation into governed production workflows.

Generative & Agentic AI

Design applied AI systems using traditional AI, GenAI, and agentic AI patterns to automate enterprise workflows and improve decisions.

Data Mesh & Data Lake Architecture

Modernize enterprise data ecosystems with scalable data products, governance patterns, cloud platforms, and analytics-ready foundations.

Predictive Analytics

Develop predictive models for device health, risk scoring, supply chain visibility, order health, and operational intelligence.

Cloud, Big Data & Streaming

Engineer scalable systems using AWS, Azure, GCP, Hadoop, Spark, Kafka, Cassandra, MongoDB, Elasticsearch, Docker, Kubernetes, Python, and Golang.

Case Studies

AI systems, platforms, and business outcomes

Selected programs that show architecture, execution, productionization, and measurable business value.

IBM Device Health Intelligence

Unified ML-driven Device Health Score using sensor data, emergency events, battery patterns, age, and usage signals to identify degrading devices earlier.

Projected ~15% reduction in emergency replacements.

Machine LearningTelemetryPredictive Intelligence

Enterprise Device Right-Sizing

Persona and workload-aware strategy to align CPU, GPU, and RAM capacity with real usage for capital planning and procurement optimization.

Expected ~8% procurement overspend reduction.

OptimizationPersona IntelligenceEnterprise AI

MLOps Framework for Production AI

Standardized production ML practices, model deployment workflows, observability, and delivery governance across enterprise ML programs.

Reduced deployment cycle from one month to under a week.

MLOpsCI/CDModel Governance

Supply Chain AI Modernization

Predictive order stages, order health monitoring, distress order management, and digital supply chain intelligence platforms.

Improved supply chain visibility and operational responsiveness.

Supply Chain AIData PlatformsDecision Intelligence

Experience

Career journey

A progression from deep engineering execution to enterprise AI architecture, MLOps leadership, and product engineering.

Product Engineering Lead

IBM • Bangalore, India

June 2025 – Present

Architecting IBM’s unified Device Health Score framework using sensor data, battery patterns, emergency events, device age, and usage signals. Building proactive device-risk engines, persona intelligence models, and enterprise-wide right-sizing strategies.

  • Designed ML-driven Device Health Score to identify degrading devices earlier.
  • Established proactive risk engine projected to reduce emergency replacements by ~15%.
  • Built persona intelligence models distinguishing technical vs non-technical users with >93% accuracy.
  • Developed device right-sizing strategy expected to reduce procurement overspend by ~8%.

Solution Architect Consultant

Dell International Services Pvt. Ltd. • Bangalore, India

Nov 2018 – May 2025

Led end-to-end solutioning for digital supply chain, AI/ML, MLOps, data architecture, and enterprise transformation programs. Drove adoption of modern platforms, AI/ML workbenches, and scalable production ML practices.

  • Accelerated ML deployment through enterprise-wide MLOps adoption.
  • Reduced model deployment time from one month to under a week.
  • Pioneered AI/ML workbench to reduce time-to-market for predictive models.
  • Improved data processing times by 25x through legacy pipeline redesign.

Principal Software Engineer / Solution Architect

Dell International Services Pvt. Ltd. • Bangalore, India

Jul 2015 – Nov 2018

Led solution architecture for supply chain intelligence platforms, predictive order stages, order health checks, GOV 2.0, and global distress order management.

  • Improved supply chain visibility through predictive order-stage solutions.
  • Strengthened system integration across Dell’s global supply chain ecosystem.
  • Mentored teams on Cassandra, Hadoop, Kafka, and large-scale data platforms.

Software Development Advisor / Technical Architect / Team Lead

Dell International Services Pvt. Ltd. • Bangalore, India

Aug 2011 – Jun 2015

Delivered complex integration and governance programs across supply chain segments while leading distributed development teams and maintaining high-quality delivery standards.

  • Delivered AOO and GOV 1.0 integration initiatives across supply chain areas.
  • Led distributed teams through complex technical delivery cycles.
  • Maintained quality and timeline discipline across enterprise programs.

Senior Consultant / Team Lead

Capgemini India Pvt. Ltd. • Mumbai, India

Jul 2010 – Aug 2011

Supported Telecom Italia programs through technical solutioning, coding standards, delivery coordination, and team leadership.

  • Improved project outcomes through technical governance and execution discipline.
  • Coordinated engineering delivery across project teams.

Consultant / DB Developer

GE India • Bangalore, India

Nov 2007 – Aug 2008

Built internal research and project management tools, supported SDLC execution, and optimized database performance through tuning, capacity planning, and issue resolution.

  • Developed internal tools supporting research and project management workflows.
  • Improved database efficiency through performance tuning and capacity planning.

Education & Credentials

Academic foundation behind applied AI leadership

2023

M.Tech in Data Science & Engineering

BITS Pilani

Advanced academic foundation in data science, machine learning, analytics, and engineering-driven AI systems.

2003

B.Tech in Computer Science & Engineering

PIET Rourkela

Core foundation in computer science, software engineering, systems design, and data technologies.

Certifications

Oracle Certified AssociateBusiness Through AI-Powered Supply Chain

Innovation

Patents, platforms, and applied AI

Filed 10 patents, including 6 granted patents listed below, across machine learning, personalization, supply chain intelligence, employee engagement, feedback analytics, and enterprise automation.

Granted Patent

Domain-driven feedback data analysis in information processing system

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Granted Patent

Hyper-segmented personalization using machine learning-based models in an information processing system

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Granted Patent

Optimized hardware product returns for subscription services

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Granted Patent

Using machine learning for individual classification

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Granted Patent

Automatically prioritizing supply chain-related demand using artificial intelligence techniques

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Granted Patent

Assistant for effective engagement of employees

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Contact

Let’s build AI that ships

Open to senior AI Leadership, AI architecture, enterprise AI, MLOps leadership, applied AI, and platform transformation opportunities.

Email: sahoo.sujit@gmail.comLinkedIn Profile