Consulting Architect - Search

Elastic Elastic · Enterprise · India · Consulting - Global - COE

This role is for a Consulting Architect focused on the Elastic Search AI Platform, specifically designing and implementing solutions involving Enterprise Search, GenAI, RAG, and vector embeddings for enterprise customers. The role involves client-facing technical consulting, solution design, proof-of-concept development, and collaboration with engineering and product teams.

What you'd actually do

  1. Work with clients to facilitate strategy, roadmap, design, and sizing in workshops.
  2. Your activities will include end-to-end delivery of ground-breaking Elastic projects to our customers, as well as development of proof-of-concepts that highlight the value of the Elastic Stack and its solutions.
  3. Daily tasks include driving and handling the objectives, requirements gathering, project tasks, project status, dependencies, and timelines, to ensure engagements are delivered optimally and on time while meeting and exceeding the customer objectives.
  4. Work across teams with engineering, product management, and support teams to identify feature improvements, extensions, and product defects.
  5. Engage with the Elastic Sales team to scope opportunities while assessing technical risks, questions, or concerns.

Skills

Required

  • Elastic Certified Engineer certification
  • 7+ years as a Consulting Architect, Senior Technical Consultant, or equivalent senior IT functional role
  • Strong history of working as a Consultant delivering professional services engagements in complex enterprise environments
  • Proven experience in deploying solutions using Elastic core domain: Enterprise Search
  • Experience in solving complex technical search problems in terms of relevancy, scaling, performance fine-tuning, building a platform to handle high query throughputs and indexing throughput, benchmarking clusters to achieve optimal performance
  • Experience in leading and delivering Enterprise Search projects at both the architectural and program level
  • Experience in GenAI, Retrieval Augmented Generation (RAG) and vector embeddings
  • Deep understanding of distributed architecture including application, database and systems
  • Hands-on experience with on-prem systems and/or major public/private cloud platforms (AWS, Azure, GCP)
  • Hands-on experience in Linux, networking, security, containerization (Docker/Kubernetes), and infrastructure automation
  • Experience utilizing programming or scripting languages in a corporate environment (e.g., Python, Javascript, Go)
  • Exceptional customer advocacy, relationship-building, and soft skills including whiteboarding and driving architectural conversations
  • Proven ability to lead and articulate technical solutions to stakeholders
  • Ability and willingness to travel to client sites periodically as required for project success (up to 20%)
  • Comfortable working effectively in a highly distributed and remote team, spanning multiple global time zones
  • BS or Master's degree in Computer Science or a related technical field

Nice to have

  • Familiarity/Experience in implementing similar products in Search Domain(Solr, Algolia, Open Search)
  • Any cloud service provider's - Gen AI certification
  • Additional Elastic Certifications (e.g., Elastic Certified Analyst, Specializations) and/or specialization in machine learning, data analytics
  • Experience working closely with a pre-sales organization in scoping customer needs and delivering against a Statement of Work (SOW)
  • Experience as a technical instructor or public speaker on enterprise infrastructure software
  • Experience contributing to an open-source project or documentation

What the JD emphasized

  • Required – Active Elastic Certified Engineer certification is mandatory.
  • Proven experience in deploying solutions using Elastic core domain: Enterprise Search.
  • Experience in GenAI, Retrieval Augmented Generation (RAG) and vector embeddings.

Other signals

  • Consulting Architect
  • Search AI Platform
  • Enterprise Search
  • GenAI
  • RAG
  • vector embeddings