Sr Architect

Job description

Area(s) of responsibility Lead pre-sales pursuits (RFPs, RFIs, proactive proposals) across AIOps, Service Assurance, Infra & Application Monitoring, Event Management, and Automation/Orchestration — including multi-tower and managed-services deals. - Architect end-to-end AIOps and observability solutions that ingest, normalize, and correlate high-volume telemetry (metrics, logs, traces, events) across cloud, on-prem, and hybrid estates to reduce client MTTD/MTTR. - Design and embed Agentic AI solutions — autonomous/multi-agent frameworks, LLM-powered and function-calling agents — into enterprise ITSM and IT/Cloud Operations workflows. - Conduct technical discovery and value-discovery workshops; convert client SLAs and reliability objectives into measurable SLIs/SLOs. - Create solution designs, architecture blueprints, effort estimates, scope of work (SoW), and pricing inputs in partnership with sales, bid, finance, and delivery teams. - Lead OEM/tool evaluations and POCs, balancing features, scale, cost, and integration complexity; leverage OEM partnerships (Aisera, ServiceNow, Dynatrace, Splunk, etc.) for joint pursuits. - Contribute to order-booking and revenue targets for the pursuit pipeline; review pricing benchmarks and effort-estimation models - Act as the technical SME and trusted advisor in client orals, solution defense, and stakeholder discussions; own objection handling and win-theme alignment. - Map client requirements into platform capabilities and a clear implementation roadmap. - Define, build, and present compelling demos and Proof-of-Value (PoV) engagements; maintain reusable demo assets and reference architectures. - Ensure a clean solution-to-delivery handover — transitioning architecture, scope, and assumptions to project/delivery teams for successful execution. - Build the practice: develop reusable solution accelerators, estimation models, capability decks, and reference documentation; mentor solution and delivery engineers on AIOps patterns and Agentic AI adoption. - 12–15 years in IT across design, engineering, implementation, and pre-sales — with 3+ years in pre-sales/solutioning of AIOps use cases for enterprise/global clients. - Strong understanding of IT operations, infrastructure management, and application performance monitoring; sound ITIL foundations. - Hands-on experience with ITSM tooling (ServiceNow preferred) and across enterprise AIOps platforms — Aisera, Moogsoft, BigPanda, ServiceNow ITOM/AIOps, HPE OpsRamp, ScienceLogic. - Scripting (JavaScript or similar), low-code/no-code platforms, and hands-on REST API integration and automation workflow experience. - Expertise integrating and leveraging data from monitoring/logging/alerting tools — Datadog, Prometheus, Grafana, ELK (Elasticsearch/Logstash/Kibana), Splunk, Nagios, Dynatrace, AppDynamics, New Relic, OpenTelemetry. - Extensive hands-on experience with at least one major cloud — AWS, Azure, or GCP; working knowledge of containers (Docker, Kubernetes). - DevOps & SRE practices and tooling — Ansible, Terraform, Jenkins, Helm, CI/CD pipelines. - Understanding of ML for IT Operations — anomaly detection, predictive analytics, event correlation, and automated root-cause analysis. - Generative & Agentic AI fluency: LLMs, embeddings, RAG, prompt engineering, multi-agent/agent-orchestration, and LLM-powered automation (AI workflows / function-calling). - Knowledge of RPA/Intelligent Automation (UiPath, Automation Anywhere, Blue Prism) is a plus.