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AI/ML + Graph Engineer
AI/ML + Graph Engineer
22
Bengaluru
Job Views:
Created Date: 2026-05-16
End Date: 2026-07-14
Experience: 5 - 8 years
Salary: 7000000
Industry: IT
Openings: 1
Primary Responsibilities :
Job Description
AI/ML + Graph Engineer
Position Details
Role: AI/ML + Graph Engineer
Experience Required: 5–8 Years
Department: AI / Engineering
Employment Type: Full-Time
Job Summary
We are looking for an experienced AI/ML + Graph Engineer to work on advanced graph-driven AI systems and intelligent orchestration engines for long-running business processes.
The ideal candidate should possess strong expertise in graph theory, knowledge graphs, ontologies, graph algorithms, and traditional AI/ML techniques including reinforcement learning and policy learning. This role focuses on building foundational and reusable intelligence layers rather than prompt-based GenAI applications.
The candidate will collaborate closely with core engineering teams to design scalable AI architectures integrated deeply with backend and orchestration systems.
Experience Requirements:
Key Responsibilities
AI/ML & Graph Systems Development
Design and develop graph-driven AI systems and intelligent orchestration layers
Build scalable knowledge graph and ontology-based architectures
Develop reusable intelligence frameworks for long-running business workflows
Implement graph algorithms and reasoning systems for decision-making engines
Machine Learning & Intelligence Engineering
Apply AI/ML techniques including:
Reinforcement Learning (RL)
Policy Learning
Decision Optimization
Domain-specific AI modeling
Fine-tune small language models (SLMs) for specialized business use cases
Build intelligent backend systems integrated with orchestration layers
Improve system adaptability, automation, and contextual reasoning
Backend & System Integration
Work closely with backend engineering and orchestration systems
Design AI systems that interact with workflows, process engines, and operational data
Develop scalable APIs, pipelines, and intelligence modules
Optimize performance and scalability of AI-driven systems
Research & Innovation
Explore advanced approaches in graph AI and knowledge-based systems
Evaluate emerging AI/ML technologies and frameworks
Contribute to architecture decisions and long-term AI strategy
Prototype and validate new intelligence capabilities
Required Qualifications
Bachelor’s or Master’s Degree in:
Computer Science
Artificial Intelligence
Machine Learning
Data Science
Related Technical Field
Experience Required
5–8 years of experience in AI/ML Engineering
Strong experience in graph-based AI systems and knowledge representation
Experience building production-grade AI systems and backend integrations
Hands-on experience with fine-tuning small language models
Required Technical Skills
Graph & Knowledge Systems
Graph Theory
Knowledge Graphs
Ontologies
Graph Algorithms
Semantic Modeling
Graph Databases (Neo4j or similar)
AI/ML Expertise
Reinforcement Learning
Policy Learning
Traditional Machine Learning Techniques
AI Decision Systems
Model Fine-Tuning & Optimization
Programming & Backend
Python
AI/ML Frameworks (PyTorch, TensorFlow, etc.)
API & Backend System Integration
Workflow/Orchestration Systems
Distributed Systems Understanding
Preferred Skills
Experience in long-running business process automation
Understanding of orchestration engines and system workflows
Exposure to agentic AI architectures
Experience designing reusable AI infrastructure layers
Strong problem-solving and systems-thinking abilities
Key Competencies
Analytical Thinking
AI Systems Architecture
Backend Collaboration
Research & Innovation
Scalability & Optimization
Problem Solving
Work Environment
Collaborative engineering-driven environment
Opportunity to work on cutting-edge graph AI systems
High-impact role in core AI architecture development