Agentic AI Developer

About Dusker AI Dusker AI specializes in benchmarking and evaluating AI agents for real-world deployment. We develop expert-driven evaluation frameworks focused on reasoning quality, reliability, adaptability, and safety across conversational and autonomous AI systems. Our mission is to help organizations build trustworthy and production-ready AI solutions.

Role Overview As an Agentic AI Developer, you will design and develop advanced AI systems that combine autonomous reasoning, retrieval, memory, and orchestration capabilities. You will work on scalable AI infrastructures and intelligent workflows that power enterprise-grade AI applications.

What You’ll Build • Autonomous AI agents for business and operational workflows • Multi-agent orchestration systems • AI copilots and workflow automation platforms • Retrieval-Augmented Generation (RAG) pipelines • Intelligent memory and context management systems • Enterprise AI integrations with APIs, databases, CRMs, and SaaS platforms • Scalable AI systems capable of planning, reasoning, and self-correction

Core Technologies & Frameworks Candidates should have hands-on experience with several of the following technologies: • Python • LangChain / LangGraph • CrewAI / AutoGen • Semantic Kernel • MCP (Model Context Protocol) • OpenAI, Claude, or Gemini APIs • Vector Databases: Pinecone, Weaviate, Chroma, FAISS • FastAPI / Flask • Docker & Kubernetes • AWS / Azure / GCP • Git & CI/CD Pipelines

Key Responsibilities • Design and develop autonomous AI agents and workflows • Build scalable multi-agent AI architectures • Integrate LLMs with external tools, APIs, and enterprise systems • Develop memory, reasoning, and context management pipelines • Optimize prompts, agent workflows, and execution reliability • Build production-ready AI systems with monitoring and observability • Collaborate with engineering and product teams to deliver AI-first solutions

Required Qualifications • Strong proficiency in Python development • Experience building LLM-powered applications • Understanding of prompt engineering, RAG systems, embeddings, and vector search • Familiarity with AI orchestration frameworks • Experience with REST APIs and cloud deployment • Strong debugging, system design, and problem-solving skills • Ability to work in fast-paced startup or innovation-driven environments

Preferred Qualifications • Bachelor’s or advanced degree in Computer Science, Artificial Intelligence, or related fields • Strong understanding of NLP, neural networks, and pattern recognition • Experience designing, implementing, and testing AI-driven systems Bonus Skills • Fine-tuning LLMs • AI evaluation frameworks • Browser automation agents • Voice AI systems • Knowledge graphs • Reinforcement learning or planning systems • Open-source AI contributions