AI Engineer at Portless developing AI-powered systems for global delivery solutions. Collaborating with teams to design and implement intelligent automation and workflow systems.
Responsibilities
Design and build AI-powered features across our B2B portal, internal tooling, and merchant-facing products — including LLM integrations, AI agents, and intelligent automations
Translate ambiguous business problems into well-scoped AI solutions, from prompt engineering and RAG pipelines to full agentic workflows
Build, evaluate, and iterate on AI systems using a rigorous experiment-driven approach — tracking quality, latency, and cost tradeoffs
Collaborate closely with product, operations, and engineering teams to identify high-leverage AI opportunities and deliver them end-to-end
Develop internal AI tooling and skill frameworks that empower non-technical teams to leverage AI in their daily workflows
Integrate with third-party AI APIs (Anthropic, OpenAI, etc.) and MCP-based tooling while maintaining security and reliability standards
Maintain observability over deployed AI systems — monitoring for regressions, prompt drift, and model performance degradation
Work independently in a remote environment with a strong sense of ownership and ability to ship with minimal oversight
Requirements
3+ years of software engineering experience, with at least 1–2 years focused on building production AI or ML systems
Hands-on experience with LLM APIs (Anthropic Claude, OpenAI GPT, etc.) and prompt engineering best practices
Strong programming skills in Python and/or TypeScript/JavaScript; comfortable building both backend services and lightweight frontend interfaces
Experience building RAG pipelines, embedding workflows, or agentic systems using frameworks like LangChain, LlamaIndex, or similar
Familiarity with vector databases (Pinecone, Weaviate, pgvector, etc.) and semantic search patterns
Experience working cross-functionally with non-technical stakeholders to scope and deliver AI projects
Proven ability to evaluate AI output quality and build evals/testing frameworks for LLM-based systems
Logistics, supply chain, or B2B SaaS experience is a strong plus
Experience with MCP (Model Context Protocol), AI agent orchestration, or multi-step tool-use workflows is a bonus
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