Senior Software Architect

· Write production-quality code across multiple technology stacks (Java, Python, TypeScript, C++)

· Implement AI/ML models using frameworks like LangChain, LangGraph, OpenAI APIs, and custom ML pipelines

· Integrate AI capabilities into existing microservices and monolithic applications

· Build APIs and services that expose AI functionality to product features

· Develop data pipelines for training, inference, and model management

· Code reviews and technical leadership for AI/ML implementations

· Design comprehensive test strategies for AI/ML systems including:

• Unit tests for AI model wrappers and data processing

• Integration tests for AI service endpoints

• Performance and load testing for AI inference pipelines

• Accuracy and validation testing for model outputs

• A/B testing frameworks for model comparison

· Implement automated testing for AI features to ensure reliability

· Validate AI outputs for correctness, bias, and edge cases

· Monitor AI system performance in production and establish alerting

· Define AI/ML architecture patterns and best practices for the organization

· Create technical documentation for AI implementations

· Mentor engineers on AI/ML best practices and pragmatic implementation approaches

· Evaluate and select AI/ML tools and frameworks based on technical merit and business value

· Design scalable AI infrastructure that can handle production workloads

· Java 17+ (Spring Boot 3.5+, microservices architecture)

· Python 3.10+ (AI/ML development, data processing)

· TypeScript/JavaScript (Angular 19, React, Node.js)

· SQL (complex queries, database optimization)

· Generative AI:

• LangChain and LangGraph for multi-agent workflows

• OpenAI API, Anthropic Claude, or similar LLM APIs

• Prompt engineering and optimization

• RAG (Retrieval-Augmented Generation) implementations

• Vector databases and embeddings

· Machine Learning:

• Scikit-learn, pandas, NumPy for traditional ML

• Model training, evaluation, and deployment

• Feature engineering and data preprocessing

• Model versioning and MLOps practices

· AI/ML Infrastructure:

• Model serving and inference pipelines

• API design for AI services

• Performance optimization for AI workloads

• Cost optimization for AI API usage

· Backend Frameworks:

• Spring Boot 3.5+ (Java microservices)

• Grails 5.3+ (legacy system maintenance)

• RESTful APIs and GraphQL

· Frontend Technologies:

• Angular 19+ (modern web applications)

• React (component-based UI)

• TypeScript, JavaScript (ES6+)

• Webpack, Vite, or modern build tools

· Database & Data Management:

• PostgreSQL, MySQL, MSSQL, Oracle

• MongoDB (NoSQL)

• Database schema design and optimization

• Data migration and ETL processes

· DevOps & Infrastructure:

• Docker and containerization

• CI/CD pipelines (Jenkins, GitLab CI)

• Gradle, Maven (build automation)

• Kubernetes (container orchestration - preferred)

· Authentication & Security:

• Keycloak, OAuth2, JWT

• Security best practices for AI systems

• Data privacy and compliance (GDPR, PII handling)

· Testing Frameworks:

• JUnit, TestNG (Java)

• pytest, unittest (Python)

• Jest, Vitest (TypeScript/JavaScript)

• Protractor, Selenium (E2E testing)

· AI/ML Testing:

• Model validation and accuracy testing

• A/B testing frameworks

• Performance benchmarking

• Bias detection and fairness testing

· C++/Qt (desktop application development)

· Groovy (build scripts, legacy systems)

· XML/XSLT (data transformation)

· GraphQL (API design)

· Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)

· 10+ years of software development experience

· 3+ years of hands-on experience with AI/ML implementation in production systems

· 5+ years of experience with enterprise Java and Spring Boot

· Proven track record of solving customer problems with measurable business impact

· ARD (Agile Requirements Designer) - Requirements management and test automation platform

· SV (Service Virtualization) - Service virtualization and API mocking platform

· TDM (Test Data Manager) - Test data management and synthetic data generation

· Nolio – Nolio Release Automation

· CDD – Continuous Delivery Director

· AI hype followers who want to add AI features just because it's trendy

· Theoretical researchers without practical implementation experience

· Developers who avoid testing or don't value quality assurance

· Solo contributors who can't work collaboratively

· Technology chasers who prioritize new tech over customer value

· Pragmatic problem solvers who use AI/ML as a tool to solve real problems

· Quality-focused engineers who write tests and ensure reliability

· Customer advocates who understand user pain points and design solutions accordingly

· Hands-on architects who can both design and implement solutions

· Value creators who measure success by business impact, not technology adoption

· This position requires to be onsite, 5 days work week

· Collaborative team environment with cross-functional teams

· Access to cutting-edge AI/ML tools and infrastructure

· Opportunity to work on multiple product lines and technologies