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The job description asks for Java, Spring Boot, Microservices, Classical Machine Learning, Regression, Classification, Decision Trees and Random Forest. Make sure your resume shows the ones you have, in the words the job uses: applicant tracking systems look for them.

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This is based in Bengaluru, Karnataka.

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Principal AI Engineer

nexocean

Bengaluru, Karnataka, India

Principal Engineer (AVP/VP) – Classical Machine Learning & Business Workflow Automation

About the Role

We are looking for an experienced Principal Engineer (AVP/VP) who combines strong software engineering expertise with hands-on experience in Classical Machine Learning, intelligent automation and enterprise workflow engineering.

This is a hands-on engineering leadership role at the intersection of Engineering, Product, Data Science and Business. The individual will be responsible for designing and developing scalable enterprise applications, integrating machine learning capabilities into business systems and building automated workflows that improve operational efficiency and business outcomes.

The ideal candidate should have a strong foundation in Java, Spring Boot, Microservices and cloud technologies, along with practical experience implementing classical ML algorithms and developing automated, data-driven business workflows.

What You'll Do

Design, develop and architect scalable enterprise applications using Java, Spring Boot, Microservices and modern frontend technologies.
Develop and integrate Classical Machine Learning models into enterprise applications to solve business problems and improve decision-making.
Work with traditional ML algorithms including Regression, Classification, Decision Trees, Random Forest, Gradient Boosting, Clustering and Anomaly Detection.
Design and implement automated business workflows to streamline complex operational processes, reduce manual intervention and improve efficiency.
Translate business requirements into intelligent, technology-driven solutions using machine learning, predictive analytics and workflow automation.
Build automation frameworks that integrate business applications, data pipelines, APIs and ML-driven decision engines.
Collaborate with Data Scientists, Product Managers, Business Analysts and Engineering teams to move ML solutions from experimentation to production.
Design and implement scalable APIs and microservices to integrate ML models and automated workflows into enterprise platforms.
Drive engineering excellence through code quality, automation, testing, performance optimisation and architectural best practices.
Provide technical leadership and engineering oversight across multiple feature teams.Skills & Experience Required
12+ years of experience in software engineering, application development and technical architecture.
Practical experience implementing Classical Machine Learning algorithms and integrating ML models into business applications.
Strong understanding of supervised and unsupervised learning techniques, including Regression, Classification, Clustering, Decision Trees, Random Forest and Gradient Boosting.
Experience developing automated business workflows, process automation solutions and intelligent decision-making systems.
Hands-on experience with Python and ML libraries such as Scikit-learn, Pandas and NumPy.
Experience integrating machine learning models with enterprise applications, APIs and backend services.
Strong understanding of data processing, feature engineering, model evaluation and deployment.
Experience with cloud platforms such as AWS, Azure or GCP.
Knowledge of CI/CD, DevOps, containerisation and automated testing frameworks.
Experience working in Agile environments and leading engineering teams in a matrix organisation.Additional Experience Preferred
Experience in banking, financial services or other large-scale enterprise environments.
Exposure to intelligent workflow automation, predictive decision systems and business process optimisation.
Experience with model deployment, monitoring, performance optimisation and production ML pipelines.
Exposure to business process management (BPM), rules engines and workflow orchestration platforms.
Experience designing high-performance, secure and resilient enterprise technology platforms.What We're Looking For

A hands-on Principal Engineer who can bridge traditional software engineering with Classical Machine Learning and business process automation.

The individual should be capable of understanding complex business problems, identifying opportunities for intelligent automation, developing ML-powered solutions and engineering them into scalable, secure and production-ready enterprise applications.

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