Python Automation Specialist

Mission: Own ongoing automation across GTM & Operations and ship AI-driven microservices that reduce manual work, increase conversion, and accelerate content velocity; move from brief → design → code → deploy in days.

Day-to-day: 

• Build and maintain Python microservices (FastAPI/Django) integrating with CRM/ESP/CMS/analytics for lead routing/scoring, content ops, and campaign orchestration;
• Design agentic workflows (function/tool calling, basic RAG, LLM tuning) for student journeys (school-matching, essay co-pilot, follow-ups, counselor handoffs);
• Ship GTM automations (generate variants, A/B tests, measure lift, auto-promote winners);
• Create ETL pipelines joining CRM / email / web analytics to compute segments/propensity/LTV and expose via APIs;
• Productionize reliability (retries, idempotency keys, circuit breakers, semantic caching, structured logging, dashboards & alerts);
• Own BAU stability (triage → fix → automate; runbooks, SLAs);
• Collaborate with Product/Content to translate brief → measurable automation with clear KPIs
• Maintain on-call hygiene with runbooks, SLAs, and feature flags / canary rollout practices

Must-haves: 

• 2–5 years professional Python in production; 
• Proven microservices delivery (FastAPI / Flask), async + queues/webhooks/integrations; 
• External API wiring (auth, pagination, rate limits, backoff, idempotency); 
• Comfort with LLM tooling (prompting, function/tool calling, basic RAG) and evals; 
• Solid SQL + basic NoSQL; 
• CI/CD (GitHub Actions), containers, monitoring; 
• “QA-first” mindset (typing, tests, perf); clear comms translating GTM brief → API + dashboard with KPIs.

Nice-to-haves: 

• LangGraph/agent orchestration; 
• rerankers; 
• vector / pgvector at scale; 
• TimescaleDB continuous aggregates; 
• LLM cost/latency budgeting; 
• Zoho (CRM / Sign / Analytics) and other CRM/ESP APIs; 
• event buses / queues (Redis / Kafka / RabbitMQ, Laravel Queues); 
• AWS / GCP / Azure; Terraform; Prometheus/Grafana; LLM/RAG for content ops 

(templating / summarization / QA); light admin UIs (React / Nuxt).

Tech context: 

• Backend: Python 3.11+, FastAPI / Django, RQ / queues, Pydantic; 
• Data: MySQL / Postgres(+Timescale) / Redis / Mongo; 
• Messaging/Orchestration: Kafka/RabbitMQ/Redis Streams, n8n; 
• Infra: Docker, K8s (RKE2), GitHub Actions CI/CD, Terraform, Prometheus/Grafana, 

Apache2; 

• GTM stack: Zoho (CRM/Sign/Analytics) or similar, ESP, Slack/Slab/ChatOps, 

GA/Hotjar; webhooks & REST.

Experience: 2–5 YOE.

Reporting: CTO; works closely with CEO and GTM team.