Job Description
We are looking for an AI Platform Senior Lead to join our engineering team and take ownership of the infrastructure, pipelines, and platform capabilities that power our AI and LLM-based solutions. This is a hands-on engineering role for someone who thrives at the intersection of cloud infrastructure, data engineering, and AI systems — not someone who builds models, but someone who builds the platforms that make AI systems reliable, observable, and scalable in production.
You will work closely with application teams, data scientists, and product stakeholders to ensure AI workloads run efficiently, cost-effectively, and at scale.
What You Will Do:
AI Platform & Infrastructure
Design, build, and maintain scalable platforms that support LLM inference, embedding pipelines, RAG systems, guardrails, and multi-tenant AI services
Architect and manage APIs and microservices that abstract AI capabilities for consumption by application teams
Own platform reliability — uptime, latency SLAs, cost per request, and performance benchmarks
Build and maintain multi-tenant infrastructure with solid isolation, quota management, and usage tracking across teams and clients
Data Engineering & Processing
Design and implement data ingestion, transformation, and processing pipelines that feed AI systems
Build and manage vector databases, document stores, and retrieval infrastructure for RAG and semantic search use cases
Ensure data quality, lineage, and governance across AI data pipelines
Optimize data pipelines for throughput, latency, and cost at scale
Cloud & DevOps
Own cloud infrastructure on AWS — including ECS/EKS, Lambda, API Gateway, S3, RDS, SQS, and AI/ML services like Bedrock and SageMaker
Implement Infrastructure as Code using Terraform or CDK
Build CI/CD pipelines for AI workloads including model serving, evaluation, and deployment automation
Manage Kubernetes clusters and containerised workloads for AI services
Observability & Operations
Implement comprehensi
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