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.

Description

Job Summary

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 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.

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About SnapFind

Founded :

2023

Type :

Products & Services

Size

Stage :

Bootstrapped

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