PP - Sr. AI Engineer with Python B. - Job2841

Summary

We are seeking a highly skilled Senior AI Engineer to join our team and play a key role in the development of our internal Agent Builder—a self-service agent builder platform. This innovative platform enables businesses to move away from heavy prompt engineering in favor of a more intuitive experience, allowing typical business users to manage custom-built workflows. The Senior AI Engineer will be instrumental in designing, developing, and maintaining this platform, ensuring it meets the diverse needs of various business departments while optimizing performance, reliability, and security.

Responsibilities

• Designing and Developing the AI Agent Builder Platform: Lead the architecture and implementation of the platform, ensuring it is scalable, maintainable, and user-friendly.
• Implementing Robust Python-based Engineering Solutions: Utilize your expertise in Python to create efficient algorithms and data processing pipelines that enhance the platform's capabilities.
• Collaborating with Cross-Functional Teams: Work closely with product managers, UX/UI designers, and other engineers to gather requirements, provide technical insights, and ensure alignment with business goals.
• Optimizing Performance, Reliability, and Security: Continuously monitor and improve the platform's performance metrics, ensuring high availability and security standards are met.
• Ensuring Adaptability for Various Business Departments: Develop features that cater to the unique needs of different departments, facilitating a seamless user experience across the organization.
• Mentoring Junior Engineers: Provide guidance and support to less experienced team members, fostering a culture of learning and innovation within the engineering team.
• Staying Updated with Industry Trends: Keep abreast of the latest advancements in AI, machine learning, and software engineering practices to ensure the platform remains competitive and cutting-edge.

Requirements

Must-Have Skills

• Python Core Engineering: Proficiency in Python programming, with a strong understanding of its libraries and frameworks. Experience in building scalable applications and data processing systems.
• Database Management: Expertise in managing and optimizing databases, particularly with SQL, PostgreSQL, and BigQuery. Ability to design efficient data models and queries to support AI-driven applications.
• AI-driven Applications: Experience in developing applications that leverage artificial intelligence, including knowledge of machine learning algorithms and their practical applications.
• Generative AI: Familiarity with generative AI techniques, including the development and deployment of models that can create content or automate tasks.
• Natural Language Processing (NLP): Strong understanding of NLP concepts and techniques, including text processing, sentiment analysis, and language modeling.
• APIs and Integrations: Experience in designing and implementing APIs for seamless integration of AI models into existing systems and workflows.
• Software Development Best Practices: Knowledge of software development methodologies, version control systems, and testing frameworks to ensure high-quality code delivery.
• Cloud Services and Infrastructure: Proficiency in cloud technologies, particularly with Docker and Kubernetes for containerization and orchestration of applications.
• Familiarity with Generative AI (GenAI), LLMs (Large Language Models), and NLP: Understanding of the latest advancements in generative AI and large language models, and their application in real-world scenarios.
• Vector Databases and Retrieval-Augmented Generation (RAG) Techniques: Experience with vector databases and techniques that enhance the retrieval of information in AI applications.
• Work with APIs and Integrations for AI Model Deployment: Ability to deploy AI models through APIs, ensuring they are accessible and functional within the broader application ecosystem.

Nice-to-Have Skills

• Automation Tools: Familiarity with automation tools that can streamline development processes, enhance testing, and improve deployment efficiency.