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Job Description:
Job Role : As a Presales Solution Architect, you will act as a trusted technical advisor to customers, partners, sales teams, and internal stakeholders. The role requires strong expertise across the Elastic platform, including Enterprise Search, Observability, and Security solutions.
You will be responsible for translating customer business challenges into scalable Elastic-based solutions, leading technical discovery, architecture discussions, demonstrations, proof-of-concepts (PoCs), and supporting successful adoption of Elastic technologies.
Responsibilities :
Serve as the technical Subject Matter Expert (SME) for Elastic Enterprise Solutions covering Search, Observability, and Security.
Engage with customers, partners, and sales teams to understand business requirements, technical challenges, and solution objectives.
Design and architect Elastic solutions aligned to customer use cases, including: Enterprise Search and AI-powered search experiences
Application, infrastructure, and cloud observability
Logging, monitoring, APM, tracing, metrics, and OpenTelemetry-based solutions.
SIEM, threat detection, security analytics, endpoint security, and incident investigation workflows
Conduct technical discovery workshops, solution presentations, whiteboarding sessions, and executive briefings.
Develop solution architectures, technical proposals, sizing recommendations, and implementation approaches.
Lead Proof-of-Concepts (PoCs), product demonstrations, and technical validations.
Respond to RFPs/RFIs by providing accurate technical and business-aligned responses.
Collaborate with Sales, Product, Marketing, and Engineering teams to drive pipeline growth and successful customer outcomes.
Build competitive positioning against alternative search, monitoring, observability, and security platforms.
Support partner enablement activities, technical training, and knowledge-sharing programs.
Mentor junior architects and presales engineers on Elastic technologies and consultative selling practices.
Support partner to Secure, maintain, and upgrade Elasticsearch clusters.
Design and implement strategies for Elasticsearch performance optimization, scalability, and efficient data utilization.
Strong expertise in data onboarding, indexing lifecycle/tier management, and performance tuning.
Can develop and optimize ingestion pipelines, including advanced Grok parsing, event processing, and indexing strategies.
Support partner to build geospatial search, aggregation, and visualization solutions.
Manage structured and unstructured data ingestion workflows.
Technical Skills :
Strong hands-on experience with Elastic Stack components: Elasticsearch
Kibana
Elastic Agent / Beats
Logstash
Fleet Management
Experience designing and implementing enterprise-scale Elastic deployments.
Strong understanding of: Data ingestion, indexing, querying, dashboards, visualization, and analytics
Search architecture and relevance tuning
Observability concepts including logs, metrics, traces, APM, SRE practices
Security operations, SIEM workflows, threat hunting, detection rules, and security analytics
Knowledge of cloud platforms (AWS, Azure, GCP), Kubernetes, containers, DevOps and CI/CD practices.
Experience with OpenTelemetry and modern observability architectures is preferred.
Understanding of data architecture, performance sizing, scalability, and high availability concepts.
Hands-on experience with AI-powered search, vector databases, semantic search, GenAI applications, and MLOps.
Design and implement Retrieval-Augmented Generation (RAG) pipelines for LLM-based applications.
Integrate LLMs with Elasticsearch search pipelines and enterprise knowledge retrieval systems.
Can define and measure RAG quality metrics and retrieval effectiveness.
Design vector indexing and embedding strategies.
Experience with Elastic Learned Sparse Encoder (ELSER) and Model Context Protocol…