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Senior Backend Engineer (Python & TypeScript, Microservices & Data Pipelines)

Full Time Senior

Job description

EquiMatch is an AI-powered M&A origination platform connecting private equity firms, search funds, corporate development teams, and M&A advisors with acquisition targets. Behind the product is a data-heavy platform: web crawlers, LLM-driven company analyzers, scoring pipelines, a unified mailbox service, and CRM integrations — orchestrated across dozens of Python and Node.js microservices.
We’re looking for a Senior Backend Engineer who is strong in Python, solid in TypeScript, and used to owning distributed systems in production. You’ll split your time between Python services and pipelines and TypeScript services built on Encore, and you’ll be expected to set technical direction, not just execute on it. We value engineers who use AI daily to move faster and build better.

Tasks

  • Design, build, and operate Python and Node.js (TypeScript/Encore) microservices: define service boundaries, APIs, data flows, and integrations.
  • Build and maintain data pipelines — crawling, enrichment, company analysis, scoring — orchestrated with Prefect.
  • Model data and optimize queries on PostgreSQL (schema design, migrations, indexing, query performance).
  • Work with asynchronous messaging (NSQ) and background job queues to build resilient, idempotent processing.
  • Integrate LLM APIs into production workflows (extraction, classification, summarization) and make them reliable, observable, and cost-efficient.
  • Own features end-to-end: requirements, technical design, implementation, testing, deployment on Railway, and monitoring.
  • Improve observability and performance across services and LLM calls: tracing, metrics, slow-query analysis, failure-rate monitoring.
  • Drive architecture decisions, write technical designs, and mentor other engineers through reviews and pairing.
  • Contribute to automation (n8n) and internal tooling where needed.

Requirements

  • 6+ years of professional backend experience, with at least 4 years of Python in production.
  • 2+ years of professional TypeScript/Node.js experience building backend services (Encore, NestJS, Fastify, Express, or similar).
  • Deep experience with modern Python tooling: async/await, type hints, FastAPI or similar, Pydantic, pytest.
  • Strong command of microservice architecture: service decomposition, API design, resiliency, idempotency, observability.
  • Production experience with PostgreSQL — schema design, migrations, query optimization.
  • Experience with message queues or workflow orchestration (Prefect, Celery, NSQ, RabbitMQ, Kafka, or similar).
  • Track record of owning systems end-to-end in production, including incidents and performance work.
  • Habitual use of AI tools in day-to-day development; ability to apply AI effectively (prompting strategies, code/test generation, agentic workflows).
  • Clear communication, ownership mindset, and a bias toward shipping.

Nice to have

  • Encore experience specifically.
  • Web scraping and crawling at scale: rate limiting, proxies, anti-bot handling, content extraction.
  • Building products on LLM APIs: structured outputs, evaluation, prompt versioning, cost/latency tuning, MCP servers.
  • LLM observability and evaluation tooling (LangWatch, Arize Phoenix, or similar).
  • Observability stacks (Grafana, Tempo, OpenTelemetry).
  • Analytics tooling (PostHog, ClickHouse).
  • Docker and cloud deployment (Railway, AWS, GCP); Infrastructure as Code basics.
  • Security best practices (OWASP, OAuth2/JWT, secrets management, GDPR-aware data handling).
  • Experience with email/CRM integrations (IMAP, Gmail API, Microsoft Graph, HubSpot/Zoho).
  • Familiarity with the M&A, private equity, or B2B data space.

Our stack

  • Backend: Python microservices, Encore (TypeScript/Node.js) services
  • Orchestration & messaging: Prefect, NSQ, background job queues, n8n
  • PostgreSQL, ClickHouse (analytics)
  • Infrastructure: Railway, Docker, GitHub Actions
  • Observability: Grafana, Tempo, LangWatch, Arize Phoenix (LLM tracing & evaluation)
  • Analytics & tooling: PostHog, Linear, internal skills/MCP system
  • AI: LLM-assisted development workflows, LLM APIs in production, MCP integrations

Benefits

  • Meaningful ownership of core systems in a small, senior team
  • Direct impact on a product used by PE firms and M&A professionals
  • Support for AI-enhanced workflows and tooling
  • Budget for learning, conferences, and hardware
  • Flexible hours and remote-friendly culture

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Required skills

kafka docker rabbitmq communication production mentoring monitoring reliability typescript ai flexible hours hubspot python aws llm automation github actions testing gcp node.js postgresql grafana railway microservice architecture microservices infrastructure as code observability web scraping fastapi celery pytest api design performance oauth2 implementation jwt incidents shipping owasp conferences data pipelines distributed systems m&a nestjs technical design classification async/await clickhouse zoho code generation deployment cost-efficiency fastify reviews express private equity corporate development proxies metrics technical designs resiliency ownership production workflows security best practices architecture decisions prefect posthog schema design indexing opentelemetry migrations message queues cloud deployment n8n llm apis extraction imap summarization linear tracing microsoft graph rate limiting workflow orchestration agentic workflows tempo crm integrations secrets management pydantic ai-enhanced workflows test generation ai tooling remote-friendly culture ownership mindset mcp servers asynchronous messaging web crawlers learning budget pairing senior team internal tooling acquisition targets encore structured outputs llm evaluation pe firms analytics tooling end-to-end features query performance llm observability arize phoenix evaluation tooling mcp integrations prompt versioning llm tracing backend experience hardware budget prompting strategies type hints search funds m&a advisors company analyzers scoring pipelines unified mailbox service nsq background job queues idempotent processing slow-query analysis failure-rate monitoring service decomposition crawling at scale anti-bot handling content extraction cost/latency tuning langwatch gdpr-aware data handling email integrations gmail api b2b data space clickhouse (analytics) internal skills/mcp system llm-assisted development workflows llm apis in production m&a professionals

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Company information

Company
EquiMatch GmbH
Location
Berlin
Germany
Posted
6 hours ago
View all jobs at EquiMatch GmbH

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