Backend (SEO) Engineer at Remote only Full Time

About Verix

Verix is a platform for verification, engagement, and trust in the age of AI. Powered by blockchain and agentic AI, Verix enables global organizations—such as Netflix, Amdocs, The Stevie Awards, Room to Read, and UNICEF—to seamlessly design, issue, and manage digital credentials for learning, enterprise skilling, continuing education, compliance, membership, and events.

With dynamic credentials that reflect recipient growth over time, modern design templates, and attached rewards, Verix empowers enterprises to drive engagement while building trust and community.

Founded by industry veterans Kirthiga Reddy (ex-Meta, MD Facebook India) and Saurabh Doshi (ex-Meta, ex-Viacom), Verix is backed by Polygon Ventures, Micron Ventures, FalconX, and leading angels including Randi Zuckerberg and Harsh Jain.

What is OptimizeGEO?

OptimizeGEO is Verix’s flagship product that helps brands stay visible and discoverable in AI-powered answers.

Unlike traditional SEO that optimizes for keywords and rankings, OptimizeGEO operationalizes AEO/GEO principles ensuring brands are mentioned, cited, and trusted by generative systems (ChatGPT, Gemini, Perplexity, Claude, etc.) and answer engines (featured snippets, voice search, and AI answer boxes).

Role Overview

We are hiring a Backend Engineer to build the data and services layer that powers OptimizeGEO’s analytics, scoring, and reporting.

This role partners closely with our SEO/AEO domain experts and data teams to translate frameworks—gap analysis, share-of-voice, entity/knowledge-graph coverage, trust signals—into scalable backend systems and APIs.

You will design secure, reliable, and observable services that ingest heterogeneous web and third-party data, compute metrics, and surface actionable insights to customers via dashboards and reports.

Key Responsibilities

• Own backend services for data ingestion, processing, and aggregation across crawlers, public APIs, search consoles, analytics tools, and third-party datasets.
• Operationalize GEO/AEO metrics (visibility scores, coverage maps, entity health, citation/trust signals, competitor benchmarks) as versioned, testable algorithms.
• Design & implement APIs for internal use (data science, frontend) and external consumption (partner/export endpoints), with clear SLAs and quotas.
• Data pipelines & orchestration: batch and incremental jobs, queueing, retries/backoff, idempotency, and cost-aware scaling.
• Storage & modeling: choose fit-for-purpose datastores (OLTP/OLAP), schema design, indexing/partitioning, lineage, and retention.
• Observability & reliability: logging, tracing, metrics, alerting; SLOs for freshness and accuracy; incident response playbooks.
• Security & compliance: authN/authZ, secrets management, encryption, PII governance, vendor integrations.
• Collaborate cross-functionally with domain experts to convert research into productized features and executive-grade reports.

Minimum Qualifications

• 4–8 years of experience building backend systems in production (startups or high-growth product teams preferred).
• Proficiency in one or more of: Python, Node.js/TypeScript, Go, or Java.
• Experience with cloud platforms (AWS/GCP/Azure) and containerized deployment (Docker, Kubernetes).
• Hands-on with data pipelines (Airflow/Prefect, Kafka/PubSub, Spark/Flink or equivalent) and REST/GraphQL API design.
• Strong grounding in systems design, scalability, reliability, and cost/performance trade-offs.

Preferred Qualifications (Nice to Have)

• Familiarity with technical SEO artifacts: schema.org/structured data, E-E-A-T, entity/knowledge-graph concepts, and crawl budgets.
• Exposure to AEO/GEO and how LLMs weigh sources, citations, and trust; awareness of hallucination risks and mitigation.
• Experience integrating SEO/analytics tools (Google Search Console, Ahrefs, SEMrush, Similarweb, Screaming Frog) and interpreting their data models.
• Background in digital PR/reputation signals and local/international SEO considerations.
• Comfort working with analysts to co-define KPIs and build executive-level reporting.

What Success Looks Like (First 6 Months)

• Ship a reliable data ingestion and scoring service with clear SLAs and automated validation.
• Stand up share-of-voice and entity-coverage metrics that correlate with customer outcomes.
• Deliver exportable executive reports and dashboard APIs consumed by the product team.
• Establish observability baselines (dashboards & alerts) and a lightweight on-call rotation.

Tooling & Stack (Illustrative)

• Runtime: Python / TypeScript / Go
• Data: Postgres / BigQuery + object storage (S3 / GCS)
• Pipelines: Airflow / Prefect, Kafka / PubSub
• Infra: AWS / GCP, Docker, Kubernetes, Terraform
• Observability: OpenTelemetry, Prometheus / Grafana, ELK / Cloud Logging
• Collab: GitHub, Linear / Jira, Notion, Looker / Metabase

Working Model

• Hybrid-remote within India with periodic in-person collaboration (Bengaluru or mutually agreed hubs).
• Startup velocity with pragmatic processes; bias to shipping, measurement, and iteration.

Equal Opportunity

Verix is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.