Agent Orchestration Engineer (Freelancer)

About Us Deccan AI Experts is a pioneering AI company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in high-quality human-curated data, AI-first operations, and advanced AI evaluation systems. Our global network of AI and software engineering experts helps train and evaluate next-generation AI models through expert technical judgment, systems engineering, and real-world AI application development. About the Role We are seeking an Agent Orchestration Engineer (Freelancer) to support advanced AI evaluation initiatives focused on multi-agent AI systems, agent orchestration frameworks, LLM workflows, AI pipelines, tool integration, reasoning systems, and AI-generated technical content evaluation. In this role, you will evaluate AI-generated agent architectures, orchestration workflows, prompt pipelines, tool-calling logic, retrieval workflows, planning strategies, and autonomous AI system designs. Your expertise will help improve AI systems designed for intelligent agents, AI automation, multi-agent collaboration, and enterprise AI applications. This position is ideal for professionals with experience in Generative AI, LLM application development, AI agents, workflow orchestration, machine learning engineering, software engineering, or AI infrastructure. Responsibilities Review AI-generated orchestration workflows, prompt chains, reasoning graphs, tool integrations, API workflows, architecture diagrams, and technical documentation. Evaluate agent planning, memory management, task decomposition, multi-agent collaboration, context management, and execution strategies. Verify AI-generated recommendations for orchestration frameworks, agent communication, error handling, monitoring, observability, and production deployment. Assess AI-generated code, workflows, and architecture for maintainability, performance, security, and production readiness. Identify orchestration bottlenecks, workflow failures, reasoning errors, integration issues, hallucination risks, and system limitations. Provide structured feedback to improve AI performance in autonomous agents, workflow orchestration, and enterprise AI systems. Review peer-developed deliverables to maintain quality and consistency standards. Requirements Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, Information Technology, Data Science, or a related field. Master's degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline is preferred. 2+ years of hands-on experience in AI engineering, machine learning, LLM application development, software engineering, AI infrastructure, or workflow orchestration. Building AI agents and autonomous workflows. Developing Retrieval-Augmented Generation (RAG) pipelines. Integrating LLMs with APIs, databases, and enterprise applications. Reviewing AI-generated workflows, orchestration logic, and system architectures. Deploying and monitoring production AI applications. Proficiency in Python and familiarity with JavaScript, TypeScript, or Go is preferred. Experience with vector databases such as Pinecone, Weaviate, Milvus, ChromaDB, FAISS, or similar technologies. Familiarity with cloud platforms (AWS, Azure, Google Cloud), Docker, Kubernetes, REST APIs, Git, CI/CD, and observability tools is preferred. Excellent analytical thinking, system design, debugging, documentation, and written English communication skills. Strong attention to detail and ability to evaluate enterprise AI solutions. Ability to work independently in a remote, fast-paced environment. Preferred Qualifications Experience building enterprise AI assistants, autonomous agents, copilots, workflow automation platforms, or AI-powered SaaS products. Experience with model evaluation, AI benchmarking, RLHF (Reinforcement Learning from Human Feedback), prompt optimization, AI safety, or LLMOps. Experience evaluating AI-generated architectures, orchestration workflows, reasoning traces, prompt libraries, or technical documentation. Familiarity with MLOps, LLMOps, AI observability, distributed systems, event-driven architectures, and enterprise integrations. Contributions to open-source AI frameworks, technical blogs, research publications, or developer communities are highly desirable. Certifications in cloud computing, AI engineering, machine learning, Kubernetes, or related technologies are advantageous. Why Join Us Competitive hourly Compensation: 1,800/hour Fully remote with flexible working hours. Opportunity to contribute to cutting-edge AI initiatives in autonomous agents, multi-agent systems, and Generative AI. Exposure to advanced AI systems focused .