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.
Shubham Vishwakarma
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