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The Role
Design, build, and operate Python and TypeScript microservices, data pipelines, integrations, and LLM-powered workflows. Own PostgreSQL data modeling, asynchronous processing, observability, performance, deployments, and production incidents end to end. Drive architecture decisions, technical designs, testing, and monitoring while mentoring engineers. The role also contributes to web crawling, CRM and email integrations, automation, and AI-enhanced development workflows.
Summary Generated by Built In
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).
* Familiarity with the qori framework.
* 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
* Data: 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, qori
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
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).
* Familiarity with the qori framework.
* 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
* Data: 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, qori
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
Skills Required
- 6+ years of professional backend engineering experience
- At least 4 years of production Python experience
- At least 2 years of professional TypeScript and Node.js backend experience
- Experience building backend services with Encore, NestJS, Fastify, Express, or similar frameworks
- Strong experience with Python async/await, type hints, FastAPI or similar, Pydantic, and pytest
- Strong command of microservice architecture, service decomposition, API design, resiliency, idempotency, and observability
- Production PostgreSQL experience, including schema design, migrations, and query optimization
- Experience with message queues or workflow orchestration such as Prefect, Celery, NSQ, RabbitMQ, or Kafka
- Track record of owning production systems end to end, including incidents and performance work
- Habitual use of AI tools in day-to-day development and ability to apply prompting, code generation, test generation, and agentic workflows effectively
- Clear communication, ownership mindset, and bias toward shipping
- Experience with Encore specifically
- Web scraping and crawling at scale, including rate limiting, proxies, anti-bot handling, and content extraction
- Experience building products with LLM APIs, structured outputs, evaluations, prompt versioning, cost and latency tuning, or MCP servers
- Experience with LLM observability and evaluation tooling such as LangWatch or Arize Phoenix
- Experience with observability stacks such as Grafana, Tempo, or OpenTelemetry
- Experience with PostHog or ClickHouse
- Familiarity with the qori framework
- Docker and cloud deployment experience with Railway, AWS, or GCP, plus Infrastructure as Code basics
- Security best practices including OWASP, OAuth2/JWT, secrets management, and GDPR-aware data handling
- Experience with email and CRM integrations such as IMAP, Gmail API, Microsoft Graph, HubSpot, or Zoho
- Familiarity with M&A, private equity, or B2B data
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The Company
What We Do
EquiMatch provides AI-powered proprietary M&A origination services for private equity firms, corporate acquirers, and M&A advisors. The company leverages AI-driven research and personalized outreach to identify, score, and engage off-market acquisition targets. By offering end-to-end sourcing—from target identification to vetted introductions—EquiMatch simplifies the merger and acquisition process and eliminates the need for large in-house analyst teams.
