Description

Key Skills: Agentic AI, Java, Python, Spring Boot, Unit Testing

Roles and Responsibilities:

1. Customer Problem Identification & Solution Design 
   1. Analyze customer feedback, support tickets, and product usage data to identify pain points and opportunities for AI/ML intervention
   2. Conduct root cause analysis of product issues and design AI-powered solutions that address underlying problems
   3. Design end-to-end solutions that integrate AI/ML capabilities seamlessly into existing product workflows
   4. Create proof-of-concepts (POCs) to validate AI solutions before full implementation
   5. Measure and demonstrate ROI of AI implementations through quantifiable metrics (time savings, error reduction, user satisfaction)
2. Hands-On Development & Implementation 
   1. Write production-quality code across multiple technology stacks (Java, Python, TypeScript, C++)
   2. Implement AI/ML models using frameworks like LangChain, LangGraph, OpenAI APIs, and custom ML pipelines
   3. Integrate AI capabilities into existing microservices and monolithic applications
   4. Build APIs and services that expose AI functionality to product features
   5. Develop data pipelines for training, inference, and model management
   6. Code reviews and technical leadership for AI/ML implementations
3. Quality Assurance & Testing 
   1. Design comprehensive test strategies for AI/ML systems including:
   2. Unit tests for AI model wrappers and data processing
   3. Integration tests for AI service endpoints
   4. Performance and load testing for AI inference pipelines
   5. Accuracy and validation testing for model outputs
   6. A/B testing frameworks for model comparison
   7. Implement automated testing for AI features to ensure reliability
   8. Validate AI outputs for correctness, bias, and edge cases
   9. Monitor AI system performance in production and establish alerting
4. Architecture & Technical Leadership 
   1. Define AI/ML architecture patterns and best practices for the organization
   2. Create technical documentation for AI implementations
   3. Mentor engineers on AI/ML best practices and pragmatic implementation approaches
   4. Evaluate and select AI/ML tools and frameworks based on technical merit and business value
   5. Design scalable AI infrastructure that can handle production workloads

Skills Required:

•  Expertise in Java 17+ with Spring Boot 3.5+ and microservices architecture.
• Strong experience in Python 3.10+ for AI/ML development and data processing.
• Proficiency in TypeScript/JavaScript, Angular 19, React, and Node.js.
• Strong SQL skills including complex query development and database optimization.
• Experience with LangChain and LangGraph for multi-agent workflows.
• Hands-on experience with OpenAI APIs, Anthropic Claude, or similar LLM platforms.
• Strong understanding of prompt engineering and optimization techniques.
• Experience implementing Retrieval-Augmented Generation (RAG) solutions.
• Knowledge of vector databases, embeddings, and semantic search technologies.
• Experience with Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
• Understanding of model training, evaluation, deployment, and MLOps practices.
• Experience designing AI inference pipelines and model-serving architectures.
• Strong knowledge of REST APIs and GraphQL.
• Experience with PostgreSQL, MySQL, MSSQL, Oracle, and MongoDB.
• Knowledge of database schema design, optimization, and ETL processes.
• Experience with Docker, Kubernetes, Jenkins, GitLab CI, Maven, and Gradle.
• Understanding of Keycloak, OAuth2, JWT, and secure application development practices.
• Strong experience with JUnit, TestNG, pytest, unittest, Jest, Vitest, Selenium, and Protractor.
• Experience with AI model validation, accuracy testing, performance benchmarking, and bias detection.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Strong QA mindset with experience in test-driven development (TDD).
• Excellent problem-solving, communication, and stakeholder management skills.
• Ability to translate customer pain points into practical and scalable AI-driven solutions.
• Experience mentoring engineering teams and providing technical leadership.

Required Qualifications

• 10+ years of software development experience.
• 3+ years of hands-on experience implementing AI/ML solutions in production environments.
• 5+ years of experience with enterprise Java and Spring Boot applications.
• Proven track record of solving customer problems with measurable business impact.
• Experience with microservices architecture and distributed systems.
• Strong understanding of MLOps practices and model lifecycle management.
• Experience working in Agile development environments.

Preferred Qualifications

• Experience with test data management or data generation systems.
• Experience with requirements management or test automation platforms.
• Knowledge of PII detection and privacy compliance standards such as GDPR and CCPA.
• Experience with synthetic data generation using AI technologies.
• Familiarity with enterprise software development lifecycle processes.
• Experience modernizing and migrating legacy enterprise systems.
• Contributions to open-source AI/ML projects.
• Published papers, technical blogs, or conference presentations related to AI/ML topics.

Note

• Candidates from IITs and IIMs are strongly preferred.
• This position requires onsite work, 5 days per week.
• Looking for pragmatic problem solvers who leverage AI/ML to solve real customer challenges and deliver measurable business value.
• Strong focus on quality engineering, testing, collaboration, and customer-centric solution development.

Education: Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.

• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline is preferred

Key Skills

Education

Any Graduate