Lead Artificial Intelligence Engineer - A/B Testing

Website : Skills : Excellent Communication Skills, Cloud platforms (AWS, Azure, GCP), CrewAI and LangChain tools, Experience in conducting A/B testing and Beta Testing, Chatbot Development Work Mode : WFH Working Day : 5 Office Location : Remote Description : Job Summary : We are seeking a visionary Senior AI Engineer with a minimum of 3 years of experience to lead the development of an advanced AI system leveraging CrewAI and LangChain tools to build intelligent, collaborative multi-agent systems for the logistics domain. The role includes designing AI agents capable of handling complex tasks, optimizing workflows, and conducting A/B and beta testing to ensure robust, scalable performance under diverse conditions. This is an opportunity to shape cutting-edge AI systems and revolutionize logistics operations. Responsibilities : 1. Design & Architecture : - Architect and implement a multi-agent AI system using CrewAI for task collaboration, communication, and real-time logistics optimization. - Integrate LangChain tools for natural language understanding, contextual reasoning, and knowledge retrieval. - Ensure the system is designed to allow comprehensive testing, iteration, and improvement. 2. AI Agent Development : - Develop autonomous agents capable of dynamic decision-making, task delegation, and seamless inter-agent communication. - Use LangChain to enhance agent capabilities, such as reasoning over unstructured data and interfacing with external knowledge bases. 3. A/B Testing & Experimentation : - Design and execute A/B tests to compare AI agent strategies, workflows, and decision-making models under varying scenarios. - Develop and implement metrics for evaluating system performance (e.g., latency, accuracy, scalability). - Use experimentation frameworks to test hypotheses and gather insights on system improvements. 4. Beta Testing & Real-World Simulation : - Set up controlled beta testing environments that mimic real-world logistics operations. - Simulate edge cases, bottlenecks, and high-load scenarios to ensure system robustness and scalability. - Gather feedback from beta users and iterate on the system to address discovered issues. 5. Progress Demonstration : - Develop dashboards and visualizations to showcase key performance indicators (KPIs) and test results. - Implement tools to log and track agent interactions, decision outcomes, and error rates in real-time. - Regularly present progress to stakeholders, highlighting improvements and areas for refinement. 6. Optimization & Scalability : - Optimize multi-agent interactions and resource allocation for real-world logistics challenges. - Ensure the system scales seamlessly for complex operations involving high volumes of agents and data. 7. Integration : - Seamlessly integrate the multi-agent system with logistics platforms, such as Transportation Management Systems (TMS) and Warehouse Management Systems (WMS). - Use LangChain tools to connect agents to APIs, external knowledge graphs, and live data streams. 8. Collaboration & Leadership : - Lead a team of engineers in developing advanced AI solutions, mentoring them on testing frameworks and innovative technologies like CrewAI and LangChain. - Collaborate with cross-functional teams to align AI development with business needs. 9. Research & Innovation : - Stay updated on the latest advancements in multi-agent systems, LangChain, CrewAI, and testing frameworks. - Introduce cutting-edge techniques to continuously improve the AI system's performance. Required Qualifications : Education : Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred ). Experience : - 3 years in AI development, with experience in multi-agent systems, logistics, or related fields. - Proven experience in conducting A/B testing and beta testing for AI systems. - Hands-on experience with CrewAI and LangChain tools. - Should have hands-on experience working with end-to-end chatbot development, specifically with Agentic and RAG-based chatbots. It is essential that the candidate has been involved in the entire lifecycle of chatbot creation, from design to deployment. - Should have practical experience with LLM application deployment. Technical Skills : - Proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch). - Strong understanding of A/B testing platforms and methodologies for AI systems. - Expertise in building beta testing pipelines and real-world simulation environments. - Familiarity with distributed systems, reinforcement learning, and natural language processing (NLP). - Proficiency in using LangChain tools for chaining tasks, knowledge retrieval, and reasoning. - Proficiency with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes). - Good to have experience in Cursor & MCP. - Experience in setting up monitoring dashboards with tools like Grafana, Tableau, or similar. Preferred Qualifications : - Experience in logistics systems, such as route optimization, shipment tracking, and demand forecasting. - Familiarity with graph theory, network optimization, and blockchain for agent security. - Background in designing scalable systems tested under diverse operational conditions. Soft Skills : - Strong analytical and problem-solving abilities. - Ability to communicate technical concepts effectively to stakeholders. - Leadership skills for mentoring teams and guiding project execution. (ref:hirist.tech)

Location: rajkot, IN

Posted Date: 3/29/2025