Lead Network SRE with IPFS

Siri InfoSolutions Inc; Jersey City (NJ); On-site; USD 130,000 - 170,000; Full time

Job summary

Siri InfoSolutions Inc is seeking a Senior Lead Site Reliability Engineer for IPFS platforms, with onsite responsibilities in Columbus, Jersey City, Plano and Houston. You will define NFRs, set SLOs, and lead reliability design and testing across services.

11+ years of experience is expected, with strong skills in observability, distributed systems, and AI-assisted workflows. You will mentor engineers, build scalable logging/metrics pipelines, and drive AI-enabled incident analysis and

Qualifications

• Formal training or certification on site reliability engineering concepts.
• Advanced knowledge in observability with SLOs, alerting, and telemetry collection.
• Proven experience building AI-assisted reliability workflows and designing logging and metrics pipelines.
• Strong ability to communicate data-based solutions and mentor others in SRE practices.

Responsibilities

• Creates and delivers high-quality designs, roadmaps, and program charters with engineering teams.
• Acts as a resource and mentor for technologists, promoting SRE culture and reliability adoption.
• Collaborates to implement observability designs for robust systems with low toil.
• Uses enterprise AI capabilities to accelerate reliability design and incident analysis.
• Drives evolution and debugging of critical components by understanding interdependencies.
• Provides guidance, tools, and solutions to support firm growth.
• Leads reuse-first AI-assisted reliability workflows across SDLC and toolchains.

Skills

SRE concepts

Observability

AI-assisted reliability

Distributed systems

Microservices

RESTful APIs

Logging pipelines

CI/CD

Tools

Grafana

Dynatrace

Prometheus

Datadog

Splunk

LangChain

LangGraph

AutoGen

CrewAI

Fluentd

Logstash

Vector

Kafka

RabbitMQ

SQS

Neo4j

TigerGraph

Pinecone

Weaviate

Chroma

Job description

Role: Lead Network SRE with IPFS

Location: Columbus, Jersey City, Plano, Houston, TX 5 Days Onsite

Contract role

Experience Required: 11-12+ Years

As a Senior Lead Site Reliability Engineer within the Infrastructure Platforms and Foundational Services (IPFS) team, you work with your fellow stakeholders to define non-functional requirements (NFRs) and availability targets for the services in your application and product lines. You will ensure those NFRs are accounted for in your products' design and test phases, that your service level indicators are effectively measuring customer experience, and that service level objectives are defined with stakeholders and implemented in production.
Job Responsibilities

• Creates and delivers high-quality designs, roadmaps, and program charters alongside the engineering team
• Acts as a key resource and mentor for technologists in your area seeking advice on technical and business issues, and serves as a culture carrier and site reliability adoption champion for your team
• Collaborates with others to create and implement observability and reliability designs for complex systems which are robust, stable, and do not incur additional toil or technical debt
• Uses enterprise-authorized AI capabilities within the work environment to accelerate reliability design and operational decisioning (e.g., incident/post-incident analysis and requirements traceability), validating outputs and handling operational data according to sensitivity and security requirements.
• Drives evolution and debugging of critical components by understanding application and platform interdependencies and limitations
• Provides comprehensive and ongoing guidance, tools, and solutions to support the firms' growth
• Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., testing/validation automation and production readiness), ensuring traceability/auditability, resiliency, and security controls.

Required Qualifications, Capabilities, And Skills

• Formal training or certification on site reliability engineering concepts and 5+ years applied experience
• Advanced knowledge in site reliability culture and principles with demonstrated ability to implement site reliability within an application or platform
• Advanced knowledge and experience in observability such as white and black box monitoring, service level objectives, alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
• Expert-level proficiency in Java, Go (Golang), Python, and Terraform for building enterprise-grade applications, high-performance systems, automation, and infrastructure as code
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve reliability engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to set team practices for safe AI usage in operations (e.g., review/approval expectations and escalation paths) while maintaining resiliency, security, and auditability outcomes.
• Advanced knowledge of software applications and technical processes with considerable depth in multiple technical disciplines including distributed systems, microservices architecture, and cloud-native technologies
• Hands-on experience building AI Agents and autonomous systems with proficiency in AI frameworks (LangChain, LangGraph, AutoGen, CrewAI) and leveraging AI development tools (GitHub Copilot, Claude, etc.) to accelerate development and innovation and Expertise in designing and implementing logging pipelines (Fluentd, Logstash, Vector) and systems for metrics collection, analysis, and distributed tracing
• Strong experience building production-grade RESTful APIs and designing message queue architectures (Kafka, RabbitMQ, SQS) for event-driven systems; and expertise in graph databases (Neo4j, TigerGraph), vector databases (Pinecone, Weaviate, Chroma), and integrating multiple data stores for AI-powered systems
• Proficiency with containerization (Docker, Kubernetes), CI/CD pipelines, and GitOps workflows
• Ability to communicate data-based solutions with complex reporting and visualization methods, recognized as an active contributor of the engineering community, and continues to expand network and leads evaluation sessions with vendors to see how offerings can fit into the firm's strategy

Preferred Qualifications, Capabilities, And Skills

• Experience with MCP (Model Context Protocol) Servers or similar agent frameworks for building autonomous systems, and understanding of LLM integration, prompt engineering, and RAG (Retrieval-Augmented Generation)
• Familiarity with AI/ML model building, deployment, and lifecycle management using frameworks like TensorFlow, PyTorch, or scikit-learn
• Experience with big data technologies (Hadoop, Spark, Flink), analytical databases, NoSQL databases (MongoDB, Cassandra, DynamoDB), and time-series databases (InfluxDB, TimescaleDB)
• Knowledge of security best practices and compliance requirements in highly regulated industries, with experience in chaos engineering tools (Chaos Monkey, Gremlin, LitmusChaos) and GameDay exercises
• Contributions to open-source projects, particularly in SRE, observability, or AI/ML domains, and certifications in cloud platforms (AWS, Azure, GCP)
• Strong communication skills with ability to mentor and educate others on site reliability principles and practices, and ability to anticipate, identify, and troubleshoot defects found during testing