Senior Lead Site Reliability Engineer (IPFS)
Core
Senior Lead SRE driving reliability, observability, and AI-assisted workflows for complex distributed systems and enterprise platforms.
Role type
Senior Lead Site Reliability Engineer (AI/Infrastructure)
Builds
Robust, stable, and secure application and platform infrastructure with reduced toil and technical debt.
Domain
Financial Services / Cloud-Native / AI Engineering
Deliverable
production ML models
Required skills
SRE culture and principles, observability (white/black-box monitoring, SLOs, alerting, telemetry), Java, Go, Python, Terraform, AI agent frameworks (LangChain, LangGraph, AutoGen, CrewAI), distributed systems, microservices, cloud-native technologies, REST APIs, message queues (Kafka, RabbitMQ, SQS), graph databases (Neo4j, TigerGraph), vector databases (Pinecone, Weaviate, Chroma), Docker, Kubernetes, CI/CD, GitOps, data visualization, vendor evaluation.
Preferred skills
on-premises data-center infrastructure, MCP servers, LLM integration, prompt engineering, RAG, AI/ML model lifecycle (TensorFlow, Pytorch, scikit-learn), big-data technologies (Hadoop, Spark, Flink), NoSQL/time-series databases, chaos engineering, open-source contributions, cloud certifications.
Technologies
AWS, Azure, GCP, Datadog, Dynatrace, Prometheus, Splunk, Grafana, Kafka, RabbitMQ, SQS, Neo4j, TigerGraph, Pinecone, Weaviate, Chroma, Docker, Kubernetes, Terraform, LangChain, LangGraph, AutoGen, CrewAI, GitHub Copilot, Claude, Fluentd, Logstash, Vector, TensorFlow, PyTorch, scikit-learn, Hadoop, Spark, Flink, MongoDB, Cassandra, DynamoDB, InfluxDB, TimescaleDB, Chaos Monkey, Gremlin, LitmusChaos, MCP servers, RAG, LLM, REST, microservices, Big Data, DevOps, Golang, Network, AI Agents, AI, Copilot, LLM, Marketing, Security, Big Data, DevOps, Golang, Network
Responsibilities
Create and deliver high-quality designs, roadmaps, and program charters; mentor technologists and champion SRE adoption; collaborate on observability and reliability designs for complex systems; use enterprise-authorized AI capabilities to improve reliability design and operational decisions; drive evolution and debugging of critical components; provide guidance, tools, and solutions supporting firm growth; contribute to SRE community; lead reuse-first adoption of AI-assisted reliability workflows; work with stakeholders to define non-functional requirements and availability targets; ensure SLOs measure customer experience effectively and are implemented in production.
