Live opening · Posted 14 days ago

AI Engineer/Architect

Aezion, Inc · Bengaluru, Karnataka, India (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 14 days ago
CompanyAezion, Inc
LocationBengaluru, Karnataka, India (Remote)
Work modeNo
SourceLinkedin
Listed14 days ago

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About the role

Description supplied by the original job listing.

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
Bachelor’s or Master’s 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.

Work arrangement
No

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