Lead technology business systems consultant

We are looking for a Senior Splunk Engineer with a strong background in API Integration to join our Observability and Infrastructure team. You will be the primary architect for our data ingestion strategies, ensuring that disparate systems are seamlessly connected to Splunk for real-time monitoring and advanced analytics.

While your core focus is on the Splunk ecosystem, we are looking for a candidate who is ready for the future of automation—specifically exploring Agentic AI to create self-healing systems and autonomous monitoring workflows.

### Key Responsibilities

• Splunk Architecture & Management: Lead the design, implementation, and optimization of large-scale Splunk environments (Indexing, Searching, and Deployment).

• Advanced API Integration: Build and maintain custom integrations using REST/SOAP APIs to pull data from cloud providers, security tools, and third-party SaaS platforms into Splunk.

• Observability Engineering: Develop complex dashboards, alerts, and reports that provide actionable insights into system health and security posture.

• Automation & Scripting: Use Python, Go, or Java to automate repetitive Splunk administrative tasks and develop custom modular inputs.

• Future-Tech Exploration (Agentic AI): Research and implement Agentic AI frameworks to move from passive monitoring to autonomous "agent-based" incident response and predictive maintenance.

• Performance Tuning: Optimize SPL (Search Processing Language) queries and data models to ensure high-speed performance across massive datasets.

### Technical Requirements

Core Requirements (Mandatory):

• Splunk Expert: Extensive experience with Splunk Enterprise, Splunk Cloud, and ITSI. Proficiency in managing Forwarders, Indexers, and Search Heads.

• Integration Specialist: Demonstrated experience building custom API integrations for data ingestion and orchestration.

• Data Lifecycle: Strong understanding of CIM (Common Information Model) mapping and data normalization.

Preferred Skills (Good to Have):

• Programming: Proficiency in at least one backend language: Python (preferred), Java, Golang, or Scala.

• AI & Innovation: Familiarity with Agentic AI concepts (e.g., AutoGPT, LangGraph, or custom autonomous agents) and how they can be applied to observability.

• Cloud Infrastructure: Experience with Splunk on AWS, Azure, or GCP.

• CI/CD: Knowledge of Git and automated deployment pipelines for Splunk apps/configurations.

### Qualifications

• Experience: 5+ years of dedicated Splunk engineering and development experience.

• Certifications: Splunk Enterprise Certified Admin or Architect is highly preferred.

• Analytical Mindset: Ability to troubleshoot complex data flows and identify "needles in the haystack" within terabytes of log data.

### Impact of This Role

In this role, you will transition our monitoring from a reactive state to a proactive, intelligent ecosystem. By combining your Splunk mastery with API expertise and emerging Agentic AI technologies, you will build the "brain" of our enterprise infrastructure.