Observability and GenAI Solution Architect

Observability And GenAI Solution Architect

Build platforms that process billions of events per day and power mission-critical decisions.

About the Role

Solution Architect

This is a senior, customer-facing role where you will design, architect and deploy next-generation observability platforms that combine open-source technologies with cutting-edge GenAI capabilities.

You will work with enterprise customers across BFSI, Digital Native, and High-Growth Tech organizations, helping them build scalable, intelligent, and resilient architectures.

What You'll Do

• Architect and build modern observability solutions using

  Elastic, OTEL Collectors, GenAI, RAG, AI Agents, Kafka

  and other open source technologies.
• Design and deploy solutions where customers ingest and query

  petabytes of data per day

  with high availability and performance.
• Build and optimize

  search, analytics, and real-time telemetry platforms

  using Elastic technology.
• Design and deploy

  GenAI-based solutions

  that support search, reasoning, enrichment, summarization, and automated insights.
• Develop new solution approaches using

  OTEL Collectors + Object Storage (S3 / MinIO / Cloud-native)

  to deliver scalable, cost-efficient architectures.
• Work closely with potential customers in pre-sales: discovery, solution shaping, architecture options, sizing and cost models.
• Present technical solutions, architecture proposals, and competitive insights to technical and business stakeholders.
• Provide L3-level technical expertise and guidance for ongoing customer engagements.

What You Bring

• 8 to 10 years of experience

  in solution architecture, data engineering, observability, or platform engineering.

• 5+ years designing and deploying Elastic Stack solutions

  in production environments.
• Strong experience in building

  Search solutions, APM, SIEM, or analytics platforms

  .
• Practical experience deploying and managing

  OTEL Collectors

  for metric/log/trace ingestion.
• Experience building platforms that handle

  large-scale data ingestion (terabytes to petabytes/day)

  .
• Hands-on experience with

  Cloud-native services (AWS, Azure, GCP)

  .
• Knowledge of Linux, Python, shell scripting, ETL pipelines, and distributed systems.
• Experience with DevOps technologies such as Ansible, Kubernetes, CI/CD.
• Understanding of building systems with Object Storage (S3, MinIO, OCI).
• Prior involvement in pre-sales, proposal creation, customer workshops, or architecture reviews is a plus.
• Curiosity and capability to

  keep up with evolving trends in GenAI, Observability and Cloud-native engineering

  .

Extra Credit

(Not mandatory, but valued)

• Experience with

  RAG architectures, embeddings, vector databases

  .
• Experience building or integrating

  AI Agents

  for automation or insight generation.
• Experience deploying

  ML algorithms for anomaly detection or predictive analytics

  .
• Certifications in Elastic, AWS, Azure, GCP, Kubernetes and related technologies.

Why This Role Matters

AI-driven observability at scale

how modern observability, telemetry, and AI systems should be built

big data, real-time analytics, distributed systems, and AI problems