AI Architect
TalentOla
- Strong experience in designing and implementing high-performance, large-scale distributed systems
- Proven experience in implementing and deploying AI/ML platforms at scale
- Expertise in building agent-based architectures, evaluation frameworks, and prompt/context engineering
- Knowledge of MCP (Model Context Protocol) servers
- Hands-on experience in LLM inference optimization, including batching and caching strategies
- Strong experience with Kubernetes and cloud infrastructure (AWS/Azure/GCP)
- Proficiency in at least one programming language (Python, Java, Go, etc.)
- Expertise in designing agent data stacks & retrieval systems, including:
- Vector databases
- Hybrid search
- Data freshness strategies
- Memory systems
- Graph reasoning
- BM25 and advanced retrieval techniques
- Architect and deliver scalable, high-performance distributed systems
- Design and deploy AI/ML and GenAI platforms at enterprise scale
- Build and manage agent-based architectures, including:
- Prompt and context engineering
- MCP servers
- Evaluation frameworks
- Optimize LLM inference pipelines for latency, throughput, and efficiency
- Design and implement agent data & retrieval systems (vector DBs, hybrid search, memory, graph-based reasoning)
- Lead Kubernetes-based, cloud-native deployments
- Provide technical leadership, architecture governance, and hands-on mentoring to engineering teams
Key Responsibilities
Vacancy posted 12 hours ago
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