Full Stack Engineer
Yellow.ai
Responsibilities
- Build and ship scalable, low-latency, cost-efficient full-stack solutions from front-end experiences to back-end services for our US-based enterprise customers.
- Design and deliver LLM-powered and agentic AI capabilities end to end: prompt orchestration, tool/function calling, retrieval (RAG / Agentic RAG), and multi-agent workflows that run reliably at scale.
- Partner closely with US customer-facing teams (Customer Success, Solutions, and Support), maintaining overlap with US business hours to unblock, troubleshoot, and deliver against customer commitments.
- Drive solutions and implementation leveraging modern web frameworks and open-source distributed systems to deliver complete, production-grade product features.
- Build innovative solutions from scratch and liaise with engineers across teams to build shared capabilities and drive adoption.
- Minimum 1+ year of experience building software products (title/level calibrated to depth of experience).
- Design and architect full-stack technical solutions for large-scale business problems.
- Hands-on experience with a modern front-end framework, React (TypeScript preferred).
- Hands-on experience in one or more back-end programming languages: Node.js / Golang / Java / Python.
- Hands-on experience building with LLMs (e. g., OpenAI, Anthropic, Google, or open-weight models); prompt engineering; function/tool calling; and streaming responses.
- Working knowledge of agentic AI concepts (tool use, orchestration, memory/context) and/or RAG with vector databases (e. g., pgvector, Pinecone, Weaviate, and Milvus).
- Good experience working with databases like MongoDB / Elasticsearch / MySQL.
- Extensive experience with Agile methodologies.
- Familiarity with modern CI/CD tools.
- Knowledge of AWS or any other cloud platform services.
- Good understanding of ML & NLP.
- Write maintainable / scalable / efficient code.
- Work in a cross-functional team, collaborating with peers during the entire SDLC.
- Follow coding standards, unit-testing, code reviews, etc.
- Follow release cycles and commitment to deadlines.
- Expertise in data structures and algorithms.
- Strong analytical skills, a bit of team management, and system design.