MulticoreWare - Full Stack Developer - Agentic Systems

Job Description :We are looking for a Full Stack Developer: Agentic Systems to build the product layer for AI-native workflows.This role focuses on turning LLMs, agents, memory, and external tools into reliable, production-grade user experiences. You will design and ship systems where agents can plan, execute multi-step tasks, recover from failures, maintain context, and deliver consistent value across sessions.Responsibilities :- Build end-to-end product features across frontend, backend, and AI integrations- Design agent workflows that support planning, tool use, failure handling, and recovery- Integrate LLMs, memory, RAG systems, and external tools into production systems- Build real-time AI interactions using streaming, partial results, and low-latency responses- Improve reliability, observability, fallback logic, and production behavior of AI workflows- Collaborate with ML, backend, product, and design teams to ship features from concept to production- Iterate on AI workflows based on user behavior, evaluation results, and observed failure modes- Establish reusable patterns for building scalable agentic systemsRequirements:- Strong full stack engineering experience across frontend and backend development- Solid understanding of system design, APIs, and production-grade architecture- Experience building with LLMs, RAG systems, agents, or AI-powered applications- Ability to work through ambiguity and make pragmatic engineering decisions- Strong ownership mindset with experience taking features from idea to productionTech Stack & Skills:Core Engineering:- Next.js, Node.js, Python- SQL and NoSQL databases- API design and backend architecture- DockerAI & Agentic Systems:- LLM integration using OpenAI, Anthropic, or open-source models- Agent workflows, tool use, memory, or RAG-based systems- Streaming responses and real-time AI interaction patterns- Agent frameworks: LangChain, LlamaIndex, CrewAI, AutoGen, or similar- Vector databases: Pinecone, Weaviate, Qdrant, Milvus, or pgvectorProduction & Reliability:- Observability, reliability, fallback handling, and debugging in production- Experience with evaluation frameworks for LLM or agent performance- Experience with workflow orchestration systemsNice to Have:- Familiarity with prompt engineering, retrieval strategies, and context management- Experience building AI products beyond chat-based interfaces (ref:hirist.tech)