Responsibilities:

- Define and articulate a clear and compelling product vision and strategy for our AIOps Platform, aligned with overall business outcomes and market opportunities.

- Conduct market research, competitive analysis, and customer discovery to identify unmet needs and emerging trends in the AIOps space.

- Translate market insights and business goals into a prioritized product roadmap.

- Build comprehensive business cases to justify new product initiatives and features, including market sizing, revenue projections, and cost analysis.

- Define clear and measurable Objectives and Key Results (OKRs) for the AIOps Platform and track product success metrics throughout the product lifecycle.

- Analyze product performance data and iterate on the product strategy based on key metrics and user feedback.

- Effectively communicate the product vision, strategy, and roadmap to internal and external stakeholders, including engineering, design, sales, marketing, and executive leadership.

- Build strong working relationships and foster a collaborative mindset across cross-functional teams to ensure alignment and shared ownership.

- Act as the voice of the customer within the organization.

- Understand the complex operational challenges faced by enterprise clients in managing their IT infrastructure and applications.

- Engage directly with enterprise clients to gather requirements, understand pain points, and validate product solutions.

- Translate enterprise client needs into actionable product features and enhancements.

- Possess a deep understanding of the Data Lifecycle Management process, from data ingestion and processing to storage, analysis, and archival within an AIOps context.

- Define data requirements and strategies for various AIOps functionalities, ensuring data quality and availability.

- Leverage your experience in building products from the ground up using open-source technologies such as the ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, Grafana, OpenTelemetry, and Kafka.

- Understand the capabilities and limitations of these technologies and how they can be effectively utilized within an AIOps platform.

- Maintain a strong understanding of applied data and AI regulations (e.g., GDPR, NIST frameworks) and ensure the AIOps Platform is designed and developed in compliance with these regulations.

- Consider privacy, security, and ethical implications in product design and development.

- Apply hands-on knowledge of data aggregation, correlation, and suppression techniques to reduce noise and surface meaningful insights from large volumes of operational data.

- Define strategies for intelligent event reduction and contextualization.

- Drive the product strategy for Analytics Process Automation, runbook automation, and agentic AI automation within the AIOps Platform.

- Understand the workflows and opportunities for automation in IT operations.

- Possess a strong understanding of the event and alarm lifecycle within IT operations, from generation to resolution.

- Define how the AIOps Platform will effectively manage, enrich, and act upon events and alarms.

- Proficiently conduct user segmentation, define target personas for the AIOps Platform, and create detailed user journey maps to understand user needs and workflows.

- Utilize user insights to inform product design and prioritization.

- Demonstrate proven experience in end-to-end Product Lifecycle Management (PLM) - from ideation and concept validation to product development, launch, growth, and eventual retirement.

- Understand Data as a Service (DaaS) models and how the AIOps Platform can leverage and potentially offer data-driven services.

- Observability and Event-Driven Architecture:

- Possess a strong understanding of observability tools, log/metric tracing, and event-driven architecture and how they contribute to a comprehensive AIOps solution.

- Have exposure to AI/ML pipelines, model governance frameworks, and MLOps practices relevant to building intelligent AIOps capabilities.

- Comfortable working with and understanding the integration of AIOps platforms with ITSM/CMDB tools like ServiceNow, BMC Remedy, or iServe.

- Comfortable working within cloud-native, microservices-based architectures and understanding DevOps principles and practices.

Must-Have Skills:

- Ability to define product vision & strategy aligned with business outcomes.

- Experience building business cases, setting OKRs, and tracking product success metrics.

- Strong stakeholder management skills and a collaborative mindset.

- Comfortable working with enterprise clients and solving real-world operational challenges.

- Deep understanding of Data Lifecycle Management - from ingestion to archival.

- Experience in building products from scratch using open-source tech (ELK Stack, Prometheus, Grafana, OpenTelemetry, Kafka, etc.

- Knowledge of applied data and AI regulations (GDPR, NIST, etc.

- Hands-on with data aggregation, correlation & suppression techniques.

- Exposure to Analytics Process Automation, runbook automation, and agentic AI automation.

- Strong knowledge of event and alarm lifecycle.

- Proficient in user segmentation, persona definition, and journey mapping.

- Proven experience in Product Lifecycle Management - ideation to scale.

- Familiarity with Data as a Service (DaaS) models.

- Understanding of observability tools, log/metric tracing, and event-driven architecture.

- Exposure to AI/ML pipelines, model governance, and MLOps.

- Experience with ITSM/CMDB tools like ServiceNow, BMC Remedy, or iServe.

- Comfortable working with cloud-native, microservices, and DevOps ecosystems.

Preferred Skills:

- Experience with specific AIOps platforms or tools.

- Understanding of machine learning algorithms relevant to AIOps.

- Experience with UX research methodologies.

- Familiarity with agile development methodologies (Scrum, Kanban).

- Excellent presentation and communication skills