高级软件工程师（后端与基础设施）

The Role
You'll own the backend, data, and infrastructure that deliver Forager's data to platform customers at scale — from ingestion all the way through to the APIs and feeds customers integrate against. This is a backend-first role: most of your time is spent building API features, operating our search and ETL data infrastructure, and owning the DevOps and platform layer underneath it. You'll also contribute to our customer-facing React/TypeScript web app, but that's the minority of the work.
This is a senior, high-ownership role on a small team. You won't just contribute features — you'll be responsible for the design, reliability, and evolution of the platform itself. You'll have direct input into product direction and the freedom (and responsibility) to ship work that materially moves our coverage, accuracy, latency, and uptime metrics.
What You'll Own
Ranked by where your time goes:

• Backend & API development — real-time enrichment APIs (person/org lookup, contact data, reverse search), search and filter endpoints, waterfall enrichment logic, and the credit/billing surfaces customers meter against. Match rate, latency, and freshness directly drive customer value.

• Data engineering, ETL & search infrastructure — own the Elasticsearch/ECK stack end-to-end (index and mapping design, ingestion pipelines, relevance tuning, cluster health, scaling, migrations), plus the ETL applications that move billions of data points daily into searchable stores, Snowflake data products, and warehouse exports while holding fill rates and accuracy.

• DevOps & platform (core owner) — you own day-to-day AWS infrastructure, infrastructure-as-code, CI/CD, and observability. This is not shared-on-the-side ops: you're responsible for infrastructure modernization, deployment pipelines, security scanning, log/metric consolidation, and the reliability of the systems you build.

• Observability & data-quality tooling — build Grafana dashboards, load tests, and data-accuracy evals that make coverage, freshness, latency, and correctness measurable and continuously monitored across the data-quality surface.

• Customer-facing web app (minority) — contribute to the React/TypeScript app, docs, onboarding, and self-serve surfaces when the work calls for it.

Core Responsibilities
Backend & API Development

• Design, build, and operate RESTful APIs for enrichment, search, feeds, and platform-customer workflows.

• Develop scalable backend services — workers, task queues, waterfall lookups, data pipelines — that keep refresh cycles predictable and fill rates high.

• Build the metering, credit-logging, and billing logic that customers rely on for accurate consumption.

• Participate actively in product planning; help shape which features have the highest customer impact.

Data Engineering, Search & ETL

• Own the Elasticsearch / ECK search stack end-to-end: index design, ingestion, relevance, cluster health, scaling, and migrations.

• Design and operate ETL applications moving data into searchable stores, bulk feeds, and warehouses (Snowflake, S3).

• Optimize PostgreSQL — query performance, indexing, cache utilization.

• Drive measurable improvements in latency, uptime, error rate, fill rate, and scalability.

DevOps & Infrastructure (Core Owner)

• Own AWS infrastructure (ECS, S3, etc.) and infrastructure-as-code.

• Own CI/CD pipelines.

• Own observability — Grafana, CloudWatch, Sentry — and on-call response for the surfaces you build.

• Drive infrastructure modernization and share crawler infrastructure maintenance with the team.

Collaboration & Quality

• Code review with high standards for readability, security, and performance.

• Write unit, integration, and E2E tests — test reliability is a quality contributor, not overhead.

• Document features, architecture, and API contracts; great developer docs are how our customers succeed.

Requirements
What We're Looking For
Required Experience

• 5+ years building and operating production backend systems and APIs, with clear examples of strategic technical problem-solving (not just tenure).

• Strong proficiency in Python / Django REST Framework.

• Hands-on experience operating Elasticsearch / OpenSearch at scale — index/mapping design, query and relevance tuning, cluster management, migrations.

• Demonstrated track record building and operating ETL pipelines that move significant data volumes reliably.

• Production experience with PostgreSQL, Redis, and async task systems (Celery / RabbitMQ or equivalent).

• Core-owner-level comfort with AWS (ECS, S3, CloudWatch), infrastructure-as-code, and CI/CD (GitHub Actions or equivalent) — you're comfortable owning the platform, not just deploying to it.

• Experience operating services in production — observability, on-call, incident response.

• Working proficiency in React / TypeScript — comfortable shipping product UI when the work calls for it. (This is the minority of the role, not its center.)

• Strong written communication; comfortable owning documentation as a deliverable.

AI & Agentic Workflows (Required)
This is non-negotiable. AI coding tools are core to how we build, and you're expected to operate effectively in an AI-augmented engineering environment. You must demonstrate strong, hands-on fluency with:

• AI coding tools (Claude Code, Cursor, Copilot, or equivalent) used daily for implementation, refactoring, and code review — while validating all generated output before it reaches production.

• Agentic workflows — designing, orchestrating, and debugging multi-step agent pipelines (e.g., research → plan → implement → verify loops, MCP server integration, tool-use design).

• Judgment about where AI helps vs. hurts — knowing when to delegate to an agent, when to write the code yourself, and how to keep an agent on rails for production work.

We evaluate this in interviews with live exercises. Candidates without demonstrable agentic workflow experience will not be considered.
Nice to Have

• Experience with Snowflake or other data warehouses.

• Background in B2B data products — enrichment, contact data, company data, search/discovery.

• Experience with data-privacy/compliance engineering — GDPR/PII handling, US state privacy regimes.

• Building MCP servers.

• Experience with web crawling, data sourcing, or large-scale ingestion systems.

• Open-source contributions or public technical writing.

Benefits

• Competitive pay for your location — calibrated to your experience and where you're based.

• Flexible working hours — we care about output and overlap, not clock-watching.

• Untracked PTO — take the time off you need; there's no accrual to count.

• Relaxed working environment — small team, high autonomy, low bureaucracy. Anyone can take an idea to production without jumping through hoops.

Originally posted on Himalayas