AI Infrastructure|Platform & Data Engineer

Bayside Solutions is seeking an AI Infrastructure|Platform & Data Engineer for a remote role. The engineer will be responsible for developing and maintaining backend features, managing Kubernetes deployments, and ensuring security and compliance in the AI infrastructure.

Responsibilities:

• Python backend - Comfortable reading and contributing to an async Python/FastAPI codebase; able to build or extend backend features as needed
• Kubernetes + Helm - EKS deployments, Helm chart authoring and maintenance, HPA, network policies, ingress config
• Experience with RAG (Retrieval Augmented Generation)
• CI/CD pipelines - End-to-end build → test → deploy pipelines; familiarity with Vessel (or similar internal image build tools)
• Infrastructure as Code - Helm, Terraform, or equivalent
• Observability - Metrics (Prometheus/Grafana or equivalents), log aggregation, pipeline failure alerting
• Evaluation & testing infrastructure - Automated RAG evaluation: retrieval quality metrics (MRR, NDCG, recall@k), answer quality benchmarks, regression suites
• Security & compliance - Secret management, mTLS cert rotation, access control audits

Requirements:

• Python backend - Comfortable reading and contributing to an async Python/FastAPI codebase; able to build or extend backend features as needed
• Kubernetes + Helm - EKS deployments, Helm chart authoring and maintenance, HPA, network policies, ingress config
• Experience with RAG (Retrieval Augmented Generation)
• CI/CD pipelines - End-to-end build → test → deploy pipelines; familiarity with Vessel (or similar internal image build tools)
• Infrastructure as Code - Helm, Terraform, or equivalent
• Observability - Metrics (Prometheus/Grafana or equivalents), log aggregation, pipeline failure alerting
• Evaluation & testing infrastructure - Automated RAG evaluation: retrieval quality metrics (MRR, NDCG, recall@k), answer quality benchmarks, regression suites
• Security & compliance - Secret management, mTLS cert rotation, access control audits
• Experience with embedding/vector search platforms at scale
• Familiarity with workflow orchestration like Airflow, Temporal etc
• Load testing and capacity planning for high-volume embedding ingestion
• Some experience and understanding of working with AI 'Agent' workflows and how they work with Platforms