Posted on: 23/05/2026
Description :
About the Role
We are looking for an experienced Artificial Intelligence Architect to lead the design, architecture, and scaling of enterprise-grade AI platforms across Predictive AI, Generative AI, and Agentic AI ecosystems.
The ideal candidate should possess deep expertise in large-scale AI/ML systems, real-time inference architectures, autonomous AI agents, and distributed AI platforms, preferably within Payments, Fintech, Fraud Risk, or large-scale digital ecosystems.
This role requires a strong technical leader capable of architecting high-throughput AI systems, driving AI platform strategy, and leading cross-functional engineering teams to deliver production-scale AI solutions with enterprise-grade reliability, governance, and scalability.
Key Responsibilities :
Architect and lead enterprise-scale AI/ML platforms across :
- Predictive AI
- Generative AI
- Agentic AI Systems
- Real-Time Intelligence Platforms
Design and scale production-grade AI systems supporting high transaction throughput and low-latency inference.
Build and optimize real-time AI/ML pipelines using technologies such as :
- Apache Kafka
- Apache Spark
- Apache Flink
- Kubernetes
- Ray
Lead the architecture and implementation of :
- LLM-powered platforms
- RAG pipelines
- Autonomous AI agents
- Multi-agent orchestration systems
Design scalable AI infrastructure for :
- Vector databases
- Feature stores
- Model serving platforms
- Distributed inference systems
Drive advanced AI engineering practices including :
- Prompt Engineering
- Fine-tuning
- Retrieval Optimization
- Inference Optimization
- AI Governance
Build and govern enterprise AI reliability frameworks including :
- Rollback mechanisms
- Guardrails
- Observability
- Monitoring
- Risk Controls
1.Lead architecture reviews, platform modernization, and AI engineering best practices.
2. Collaborate with Product, Risk, Fraud, Platform, and Engineering teams to align AI strategy with business goals.
3. Mentor and lead cross-functional AI/ML and platform engineering teams.
4. Stay updated with emerging AI technologies, frameworks, and industry innovations.
Required Skills & Qualifications :
13+ years of experience in :
- AI/ML Architecture
- Enterprise AI Platforms
- Distributed Systems
- Large-Scale Data & ML Engineering
Strong domain experience in :
- Payments
- Fintech
- Fraud Risk
- Digital Ecosystems
Proven expertise in :
- Predictive AI
- Generative AI
- Agentic AI
- Real-Time AI Systems
Strong hands-on experience with :
- PyTorch
- TensorFlow
- Transformers
- GNNs
- XGBoost
- LightGBM
Deep expertise in :
- LLMs
- RAG Architectures
- Vector Databases
- Prompt Engineering
- Autonomous AI Agents
- Fine-Tuning Techniques
Strong experience designing and scaling AI systems using :
- Kafka
- Spark/Flink
- Kubernetes
- Ray
- Feature Stores
Experience managing large-scale AI platforms handling :
- 10,000+ TPS
- Low-latency inference
- Enterprise reliability requirements
Strong understanding of :
- AI Governance
- Model Monitoring
- AI Observability
- Risk & Compliance Controls
Proven leadership experience managing AI/ML and platform engineering teams
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