Diversity Nexus · 4 months ago
LLM/Prompt-Context Engineer – Fullstack Python (AI Agents, LangGraph, Context Engineering)
Diversity Nexus is seeking a highly skilled LLM/Prompt-Context Engineer with a strong fullstack Python background. The role involves designing, developing, and integrating intelligent systems focused on large language models (LLMs), prompt engineering, and advanced context management.
Staffing & Recruiting
Responsibilities
Design, optimize, and evaluate prompts for LLMs to achieve precise, reliable, and contextually relevant outputs across a variety of use cases
Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization, to enhance agent performance
Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment
Build and manage complex conversational and agent workflows using the LangGraph framework to support multi-agent or multi-step solutions
Develop robust backend services, APIs, and (optionally) front-end interfaces to enable end-to-end AI-powered applications
Work closely with product, data science, and engineering teams to define requirements, run prompt experiments, and iterate quickly on solutions
Implement testing, monitoring, and evaluation pipelines to continuously improve prompt effectiveness and context handling
Qualification
Required
Deep experience with full stack Python development (FastAPI, Flask, Django; SQL/NoSQL databases)
Demonstrated expertise in prompt engineering for LLMs (e.g., OpenAI, Anthropic, open-source LLMs)
Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies
Hands-on experience integrating AI agents and LLMs into production systems
Proficient with conversational flow frameworks such as LangGraph
Familiarity with cloud infrastructure, containerization (Docker), and CI/CD practices
Exceptional analytical, problem-solving, and communication skills
Preferred
Experience evaluating and fine-tuning LLMs or working with RAG architectures
Background in information retrieval, search, or knowledge management systems
Contributions to open-source LLM, agent, or prompt engineering projects
Company
Diversity Nexus
Funding
Current Stage
Growth StageCompany data provided by crunchbase