Varanasi, Uttar Pradesh, India
Information Technology
Full-Time
Recruire
Overview
Responsibilities
Education : Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
Experience
- 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.
- AI Agent Development :
- Use LangChain to enhance agent capabilities, such as reasoning over unstructured data and interfacing with external knowledge bases.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
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.
- 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.
- 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.
- Strong analytical and problem-solving abilities.
- Ability to communicate technical concepts effectively to stakeholders.
- Leadership skills for mentoring teams and guiding project execution.
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