At a Glance
- Tasks: Design and implement scalable systems and data pipelines for our core product.
- Company: Join a VC-backed, remote-first startup tackling cybersecurity challenges with Generative AI.
- Benefits: Work remotely and be part of a founding team with significant growth potential.
- Why this job: Contribute to impactful work in cybersecurity while collaborating with an expert team from Big Tech.
- Qualifications: Strong backend development skills in Python, Java, Go, or Node.js; experience with data pipelines and distributed systems.
- Other info: Be at the forefront of innovation in cybersecurity and help drive better outcomes for companies.
The predicted salary is between 43200 - 72000 £ per year.
As our Founding Engineer with a specialization in machine learning data engineering and model implementation, you’ll have great experience building data pipelines and distributed processing systems. You’ll be responsible for designing and implementing robust, scalable systems, and efficient distributed processing frameworks that will power our core product. We are a VC backed, remote-first business looking to complete our Founding Team. Why Join Us: Ambitious Challenges: We are using Generative AI (LLMs and Agents) to solve some of the most pressing challenges in cybersecurity today. You’ll be working at the cutting edge of this field, aiming to deliver significant breakthroughs for security teams. Expert Team: We are a team of hands-on leaders with deep experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO. Impactful Work: Cybersecurity is becoming a challenge to most companies and helping them mitigate risk ultimately helps drive better outcomes for all of us. What You Need to Be Successful: Extensive Experience in backend development: Strong proficiency in backend languages and frameworks such as Python, Java, Go, or Node.js, and experience with building microservices. Data Pipeline Mastery: Expertise in building and optimizing data pipelines using tools like Apache Kafka, Apache Spark, or AWS Glue. Distributed Systems Knowledge: Experience designing and implementing distributed systems for parallel data processing, with a strong understanding of tools like Hadoop, Spark, or Flink. Database Proficiency: Deep knowledge of both relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Cassandra, MongoDB), with experience in designing scalable database architectures.
Founding Backend Engineer employer: Heart Mind Talent
Contact Detail:
Heart Mind Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Backend Engineer
✨Tip Number 1
Make sure to showcase your experience with backend development and the specific languages mentioned in the job description. Highlight any projects where you've built microservices or worked with data pipelines, as this will demonstrate your fit for the role.
✨Tip Number 2
Familiarize yourself with the latest trends in machine learning and cybersecurity. Being able to discuss how generative AI can impact security challenges will show that you're not just technically skilled but also aligned with our mission.
✨Tip Number 3
Prepare to discuss your experience with distributed systems and the tools listed, like Hadoop or Spark. Be ready to share specific examples of how you've designed and implemented these systems in past roles.
✨Tip Number 4
Network with professionals in the cybersecurity and data engineering fields. Engaging with communities on platforms like LinkedIn or GitHub can provide insights and connections that may help you stand out during the interview process.
We think you need these skills to ace Founding Backend Engineer
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your extensive experience in backend development and your proficiency in languages like Python, Java, Go, or Node.js. Tailor your CV to showcase projects where you've built microservices.
Showcase Data Pipeline Mastery: Detail your expertise in building and optimizing data pipelines. Mention specific tools you have used, such as Apache Kafka, Apache Spark, or AWS Glue, and provide examples of how you've implemented these in past projects.
Demonstrate Distributed Systems Knowledge: Include information about your experience with distributed systems and parallel data processing. Highlight any relevant projects where you utilized tools like Hadoop, Spark, or Flink.
Database Proficiency: Discuss your deep knowledge of both relational and NoSQL databases. Provide examples of scalable database architectures you have designed, mentioning specific databases like PostgreSQL, MySQL, Cassandra, or MongoDB.
How to prepare for a job interview at Heart Mind Talent
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with backend languages and frameworks like Python, Java, Go, or Node.js. Highlight specific projects where you built microservices or optimized data pipelines, as this will demonstrate your technical proficiency.
✨Demonstrate Data Pipeline Mastery
Discuss your experience with tools such as Apache Kafka, Apache Spark, or AWS Glue. Be ready to explain how you've built and optimized data pipelines in previous roles, as this is crucial for the position.
✨Understand Distributed Systems
Make sure you can articulate your knowledge of distributed systems and parallel data processing. Prepare examples of how you've designed and implemented these systems using tools like Hadoop, Spark, or Flink.
✨Highlight Database Proficiency
Be ready to talk about your experience with both relational and NoSQL databases. Discuss how you've designed scalable database architectures and any challenges you've faced in this area.