AI Engineer Data APIs

Benzinga, a prominent financial media company renowned for its insights into stock market trends and opportunities, is seeking to expand its technical team with a talented AI Engineer focused on Data APIs. This is a remote opportunity, offering flexibility for skilled professionals to contribute to a dynamic and innovative environment. The company fosters a culture of continuous improvement and is looking for individuals who are not only technically adept but also passionate about solving complex challenges.

About the Role

This position is central to Benzinga's ongoing development and integration of artificial intelligence into its data-driven platforms. The AI Engineer, Data APIs, will be instrumental in building and refining the vital interfaces that connect AI applications with the vast datasets Benzinga manages. This role requires a deep understanding of both AI principles and robust API design, ensuring that data can be accessed, processed, and leveraged efficiently and effectively. The successful candidate will play a key role in shaping the technical direction of data services, contributing to the company's ability to deliver cutting-edge financial information and analysis.

The core of this role revolves around the design, development, and maintenance of high-quality data APIs specifically tailored for AI applications. This involves:

• **API Development and Maintenance:** Creating, deploying, and supporting robust and scalable data APIs that serve as the backbone for various AI initiatives within Benzinga. This includes ensuring the APIs are secure, performant, and reliable.
• **Cross-functional Collaboration:** Working closely with product managers, data scientists, and other engineering teams to thoroughly understand their data requirements and translate these needs into effective API solutions.
• **Architectural Leadership:** Driving critical architectural decisions related to data pipelines, API design patterns, and infrastructure. This involves evaluating different approaches, understanding trade-offs, and advocating for best practices.
• **Technical Guidance:** Providing mentorship and technical expertise to fellow developers, fostering a collaborative learning environment, and promoting high standards of code quality and engineering excellence.
• **Problem Solving:** Tackling complex technical challenges, particularly those at the intersection of data, AI, and API development, and devising innovative solutions.

What They're Looking For

Benzinga is seeking an individual with a strong foundation in AI and a proven track record in API development. Essential qualifications and attributes include:

• **AI and API Expertise:** Demonstrable experience in developing and implementing AI solutions, coupled with significant expertise in designing and building data APIs.
• **Programming Proficiency:** Strong command of programming languages commonly used in AI and backend development, such as Python or Go.
• **Data Architecture Understanding:** A solid grasp of data architecture principles, including data modelling, database technologies, and data flow management.
• **Cloud Services Familiarity:** Experience with cloud platforms and their associated services relevant to data storage, processing, and API deployment.
• **Communication Skills:** The ability to clearly articulate complex technical concepts to both technical and non-technical stakeholders.
• **Problem-Solving Acumen:** A proactive approach to identifying and resolving technical issues, with a focus on architectural considerations and trade-offs.

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In South Africa, AI engineering roles, particularly those involving data APIs and cloud technologies, are in high demand. While specific remuneration varies greatly based on experience, location within SA (though this role is remote), and the complexity of the systems involved, a mid-level to senior AI Engineer could typically expect a competitive salary package. Employers in this space often include financial services firms, tech startups, established software companies, and consulting firms. Career progression often involves moving into more specialised AI fields, leading engineering teams, or transitioning into architecture or product management roles.

• Strong experience in AI and API development.
• Proficiency in languages such as Python or Go.
• Understanding of data architecture and cloud services.
• Ability to communicate technical concepts clearly.