Lead AI Engineer - Python/Machine Learning

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 :

- 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.