Website:
marseerai.com
Job details:
About Marseer AI
Marseer AI is a Seattle, Washington (US) based company building AI products used by the marketing teams of leading brands. Our platform is a modular AI activation system for DTC and retail e-commerce brands, anchored by a Brand Strategy Module that defines a brand's identity, voice, and strategic priorities. Every channel module inherits that context to drive consistent, data-driven customer engagement across email, SMS, paid media, SEO, and affiliate channels.
The Marseer Marketing Intelligence Platform is the AI brain behind the system: an agentic, LLM-powered suite of strategist agents that analyze brand data, decide what actions to take, generate content and campaign variants, and continuously optimize performance across channels.
Role Overview
We're looking for an experienced AI Engineer / Full Stack Developer to join the Marseer platform team. This is a backend- and AI-first role with a full-stack surface: you'll build and maintain AI agent pipelines, LLM integrations, and RAG-based intelligence systems, and surface the resulting insights, recommendations, and campaign outputs in the product interfaces used by marketing teams.
Your core strength is backend and AI engineering, but you're comfortable enough on the frontend to take a feature all the way to a working UI. You know how to engineer prompts and tool chains for reliability, and you care about the end-to-end user experience.
What You'll Do
AI Engineering & Agent Development
- Design and implement multi-step AI agent workflows using LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI)
- Build and maintain RAG pipelines, including chunking strategies, embedding generation, vector store management, and retrieval tuning
- Integrate with LLM providers (OpenAI, Anthropic, and others), covering prompt engineering, tool/function calling, structured output, and context window management
- Develop AI-driven features such as campaign brief generation, audience recommendation, content variant creation, and performance insight summarization
- Design agentic systems that autonomously analyze marketing data, generate recommendations, and trigger downstream actions across channels
- Implement evaluation and observability frameworks to monitor LLM output quality, latency, and cost in production
Full Stack Development
- Build and maintain 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 the frontend with backend AI services, streaming LLM responses, and real-time status updates
- Own the full feature lifecycle, from technical design through implementation, testing, and deployment
- Ensure UI components are performant, accessible, and consistent with design system standards
Data & Integrations
- Work with structured and unstructured marketing data: campaign performance metrics, audience segments, content libraries, and brand strategy documents
- Integrate with third-party marketing platforms and data sources (e.g., Klaviyo, Google Ads, Meta, Shopify) to feed the intelligence layer
- Collaborate with the data engineering team to consume Snowflake-sourced customer signals and segment outputs
Collaboration & Communication
- Work directly with client brand teams to understand marketing workflows, gather feedback, and translate requirements into product features
- Communicate technical decisions and AI system behaviors clearly to non-technical marketing stakeholders
- Participate in architecture reviews, contribute to technical design documents, and maintain clear documentation of AI systems and APIs
Requirements
Must-Have
- 6+ years of professional software engineering experience, with strong backend depth and the ability to work across the stack
- Strong proficiency in at least one modern backend language (Python, Node.js/TypeScript, Java/Kotlin, or similar), and willing to work in Python where our AI/LLM stack calls for it
- Hands-on experience with LLM orchestration frameworks (LangChain, LangGraph, CrewAI, Autogen, or equivalent)
- Experience building RAG pipelines, including vector stores (Pinecone, Weaviate, pgvector, or similar), embedding models, and retrieval strategies
Strongly Preferred
- Experience building and deploying LLM-powered applications in production (strong applied AI work, including substantial side projects, also counts)
- Comfortable building frontend interfaces in React or a comparable modern framework (Next.js a plus)
- Experience designing 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 (SSE, WebSockets)
- Prior work in a SaaS product company, shipping production features
- Familiarity with marketing platforms, e-commerce data, or martech ecosystems
- Experience with API design (REST or GraphQL) and backend service architecture
Good to Have
- Exposure to TypeScript and modern frontend tooling (Tailwind CSS, shadcn/ui, etc.)
- Familiarity with Snowflake or other cloud data warehouses as a data source for AI pipelines
- Experience with observability tools for LLM applications (LangSmith, Helicone, Arize, or similar)
- Understanding of marketing concepts such as segmentation, campaign lifecycle, attribution, and content personalization
You don't need to tick every box. If you're a strong senior engineer who has shipped real software and built genuine AI/LLM features, we'd love to hear from you. We hire for what you've built and how you think, not for specific titles or degrees.
What We're Looking For in You
- Availability to work US business hours, with overlap with US Eastern or Pacific timezone for client collaboration and team standups
- Strong written and verbal English communication; you will regularly interact with client brand teams and explain AI system behavior to non-technical stakeholders
- Product sense: you think about the user experience of AI features, not just whether the model output is correct
- Ownership mindset: you take features end-to-end, flag issues early, and drive problems to resolution
- Comfort with ambiguity: LLM-powered systems are non-deterministic, and you know how to design for reliability and graceful degradation
- Collaborative: you work well across engineering, design, and client-facing functions in a distributed team
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
Role Details: Full-time | 6 - 15 years experience | Fully remote (Hyderabad, India preferred) | US timezone overlap required | Competitive compensation
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