AI/ML Architect

AI Architect/Engineer

Fulltime

Bengaluru

Key Responsibilities

• Design, develop, and deploy AI/ML solutions that solve complex business problems.
• Build and optimize supervised and unsupervised machine learning models for classification, prediction, clustering, anomaly detection, recommendation systems, and pattern recognition.
• Evaluate business use cases and determine the most suitable algorithms, models, and architectures based on data characteristics and desired outcomes.
• Architect and implement multi-agent AI systems using modern orchestration frameworks.
• Develop intelligent workflows using frameworks such as LangGraph, LangChain, Microsoft Agent Framework, and related ecosystems.

Build enterprise-grade natural language query systems such as:

• NL2SQL
• NL2Cypher
• NL2GraphQL
• Design and integrate data platforms leveraging:
• Relational databases
• Columnar databases
• Document stores
• Graph databases
• Vector databases (preferred)
• Establish observability, monitoring, tracing, and debugging capabilities for AI/agent systems.
• Ensure AI systems are secure, scalable, resilient, and production-ready.
• Implement governance and compliance controls within agent systems, including access policies, guardrails, auditability, and regulatory alignment.
• Apply strong software engineering principles, design patterns, and architectural best practices to AI solutions.
• Collaborate with cross-functional teams including product, engineering, data, and business stakeholders.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, Engineering, or related field.
• 8+ years of experience in software engineering, data science, machine learning, or AI engineering roles.
• Strong expertise in Machine Learning fundamentals, including:
• Supervised Learning
• Unsupervised Learning
• Feature Engineering
• Model Evaluation
• Hyperparameter Tuning
• Drift Detection / Model Monitoring
• Deep understanding of when to use which ML algorithm based on problem type, dataset quality, scale, and explainability needs.
• Hands-on experience with Python and ML libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience with modern AI orchestration frameworks such as:
• LangGraph
• Microsoft Agent Framework
• Similar agentic AI platforms
• Strong knowledge of data storage technologies:
• SQL / Relational databases
• NoSQL / Document stores
• Columnar warehouses
• Graph databases
• Experience designing secure and scalable distributed systems.
• Solid understanding of software design patterns and enterprise architecture patterns.