About Marseer AI
Marseer AI (www.marseerai.com) is a Seattle-based company building an AI-powered marketing intelligence platform for DTC and retail e-commerce brands. The platform combines brand strategy, customer data, automation, and generative AI to help marketing teams drive consistent, data-driven engagement across email, SMS, paid media, SEO, and affiliate channels.
Role Overview
We are looking for an experienced AI Engineer - Full Stack Developer to join the Marseer platform team. This is a dual-track role: you will build and maintain AI agent pipelines, LLM integrations, and RAG-based intelligence systems on the backend, while also owning frontend interfaces that surface insights, recommendations, and campaign outputs to marketing teams and brand operators.
You should be equally comfortable designing multi-step agentic workflows in Python and building clean, responsive product interfaces in React/Next.js. You understand how LLMs behave in production, know how to engineer prompts and tool chains for reliability, and care deeply about the end-to-end user experience.
What You Will Do
- Design and implement multi-step AI agent workflows using LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar.
- Build and maintain RAG pipelines, including chunking strategies, embedding generation, vector store management, and retrieval tuning.
- Integrate with LLM providers such as OpenAI, Anthropic, or others, including prompt engineering, tool/function calling, structured output generation, and context window management.
- Develop AI-driven features such as campaign brief generation, audience recommendations, content variant creation, and performance insight summarization.
- Implement evaluation and observability frameworks to monitor LLM output quality, latency, and cost in production.
- Build frontend interfaces using React and Next.js, including dashboards, agent interaction UIs, campaign builders, and insight surfaces.
- Design and implement RESTful and/or GraphQL APIs in Python (FastAPI or Flask) or Node.js to serve AI outputs to the frontend.
- Integrate frontend with backend AI services, streaming LLM responses, and real-time status updates.
- Work with structured and unstructured marketing data, campaign performance metrics, audience segments, content libraries, and brand strategy documents.
- Integrate with marketing platforms and data sources such as Klaviyo, Google Ads, Meta, and Shopify.
Requirements
- 5-10 years of professional software engineering experience, with meaningful time in both backend and frontend development.
- Proven experience building and deploying LLM-powered applications in production, not just prototypes.
- Strong proficiency in Python for backend and AI development.
- Strong proficiency in React and Next.js for frontend development.
- Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
- Experience building RAG pipelines, vector stores such as Pinecone, Weaviate, pgvector, or similar, embedding models, and retrieval strategies.
- Experience with API design, REST or GraphQL, and backend service architecture.
Strongly Preferred
- Experience designing and building multi-agent or agentic AI systems with tool use, memory, and planning capabilities.
- Familiarity with prompt engineering best practices, structured output generation, and LLM evaluation methodologies.
- Experience with streaming LLM responses and real-time UI updates using SSE or WebSockets.
- Prior work in a SaaS product company shipping production features.
- Familiarity with marketing platforms, e-commerce data, or martech ecosystems.
Good to Have
- TypeScript and modern frontend tooling such as Tailwind CSS or shadcn/ui.
- Familiarity with Snowflake or other cloud data warehouses as data sources for AI pipelines.
- Experience with observability tools for LLM applications such as LangSmith, Helicone, Arize, or similar.
- Understanding of marketing concepts such as segmentation, campaign lifecycle, attribution, and content personalization.
What We Are Looking For
- Availability to work US business hours; overlap with US Eastern or Pacific timezone is required for client collaboration and team standups.
- Strong written and verbal English communication.
- Product sense and ownership mindset.
- Comfort with ambiguity in non-deterministic LLM-powered systems.
- Collaborative working style across engineering, design, and client-facing functions.
What We Offer
- Competitive compensation based on experience.
- Fully remote role; work from anywhere in India, with Hyderabad-based candidates preferred.
- High-impact work at the frontier of applied AI for marketing and e-commerce.
- Direct exposure to real brand problems, real data, and real production AI systems.
- A small, senior team where your architecture decisions matter and your contributions are visible.
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