Full Stack Engineer (Onsite, Lahore, USD Salary)
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Summary
Onsite full stack engineer in Lahore building an early-stage B2B SaaS ads/marketing data platform: Django APIs and React/Vite frontend, LLM agent workflows orchestrated with LangGraph/MCP, integrations with Google Ads, Meta Ads and GA4, all deployed on GCP (Cloud Run, Cloud SQL).
Requirements
- 3+ years of experience building production‑grade web applications across both backend and frontend.
- Strong proficiency in Python, preferably with Django (or a comparable framework), and experience designing RESTful APIs.
- Solid experience with React, including component‑based architecture, state management, and modern build tools such as Vite.
- Hands‑on experience with agentic AI and LLMs, including model APIs, prompt engineering, orchestration frameworks (e.g., LangGraph, LangChain, or similar), and tool calling or MCP.
- Experience with DevOps practices on a major cloud platform, including containerized deployments, managed databases, secrets management, and CI/CD pipelines.
- Experience with GCP (Cloud Run and Cloud SQL) is a strong plus.
- Strong SQL skills and a solid understanding of data modeling, particularly with PostgreSQL.
- An ownership mindset, with the ability to thrive in an early‑stage environment with shifting priorities and high impact.
- Experience working with the advertising and marketing data ecosystem, including Google Ads, Meta Ads, and GA4.
- Familiarity with the Model Context Protocol (MCP) and tool‑augmented AI agents.
- Experience with TypeScript, Cloudflare, observability tools (e.g., Datadog), or background task systems.
- Experience working on a multi‑tenant B2B SaaS product.
Responsibilities
- Build end‑to‑end features by designing Django models and APIs, then bringing them to life in the React/Vite frontend.
- Work on our agent layer by integrating and orchestrating LLM‑driven workflows with LangGraph, while connecting tools and data sources through MCP.
- Develop and maintain integrations with Google Ads, Meta Ads, GA4, and Search Console, including OAuth flows and API quota management.
- Own deployments on GCP by shipping services to Cloud Run, managing Cloud SQL and secrets, and ensuring a reliable deployment pipeline.
- Improve system performance and reliability by profiling bottlenecks, optimizing databases and connection pooling, and hardening the platform as it scales.
- Collaborate with the product team to turn ambiguous requirements into shipped features and participate in code reviews.