Senior Backend Engineer - Data Engineering & AI/LLM Focus at Collaboration.Ai
Who We’re Looking For:
We are seeking a talented and experienced Senior Backend Engineer with a strong focus on data engineering and AI/LLM integrations. In this critical role, you will be responsible for designing and developing scalable, secure, and high-performance backend systems, data pipelines, and APIs that drive our intelligent applications and agentic workflows.
You will lead the charge in creating solutions for raw data capture, web scraping, data processing, transformation, and storage, ensuring seamless integration with our advanced AI/LLM systems. Your expertise in Python, data engineering, and backend architecture will be essential as we expand our platform.
If you are a backend engineer passionate about solving complex data challenges, building high-performance systems, and working with cutting-edge AI/LLM technologies, we’d love to connect with you!
Why You Should Join Us:
This is a unique opportunity to play a foundational role in shaping the backend and data engineering infrastructure of a company at the forefront of AI innovation. You’ll have the chance to build our core systems from the ground up, directly influencing the success of our AI-driven products. You’ll work with state-of-the-art technologies, tackle exciting data challenges, and collaborate with a team of driven engineers. If you’re ready to elevate your backend and data engineering expertise and help shape the future of AI, apply today!
Your Key Responsibilities:
- Backend Architecture & Development (Data & AI Focus):
- Design, develop, and maintain high-performance backend systems, microservices, and data pipelines.
- Lead the creation of solutions for raw data capture, web scraping, data processing, cleaning, and transformation to prepare data for LLM/Agent integration.
- Build and implement APIs for data access, processing, and integration with frontend applications and AI/LLM systems.
- Contribute to the scalability and architecture of our backend infrastructure and data platform.
- Data Engineering & Pipeline Optimization:
- Design, build, and optimize data pipelines for efficient data ingestion, processing, and storage.
- Work with various data storage technologies, including RDBMS, NoSQL databases, GraphDBs, and vector/RAG storage solutions.
- Implement data quality checks and monitoring to ensure data reliability and integrity.
- Optimize data pipelines for performance, scalability, and cost-efficiency.
- AI/LLM System Integration:
- Develop and maintain backend services that integrate with AI/LLM models and agentic frameworks.
- Design APIs and data flows to support the deployment, monitoring, and scaling of AI/LLM applications.
- Collaborate with AI/ML engineers to optimize data pipelines and infrastructure for AI workloads.
- Security & Compliance:
- Implement robust security practices for backend systems and data handling to ensure system integrity and data security.
- Work with DevOps and security teams to meet compliance standards (e.g., NIST frameworks, SOC2).
- Establish data access controls and security measures to protect sensitive information.
- Mentorship & Collaboration:
- Mentor junior engineers and participate in code reviews and architectural discussions.
- Collaborate effectively with cross-functional teams (frontend, AI/ML, product) in an agile environment.
- Promote best practices in backend development, data engineering, and security.
Basic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 7+ years of professional experience in backend development, with proficiency in Python and experience in strongly-typed languages (e.g., Kotlin, Java, Go, or Rust). We value engineers with experience in both dynamically-typed and statically-typed languages.
- Extensive experience in data engineering principles and building robust data pipelines.
- Proven expertise in designing and developing scalable, secure backend systems and microservices.
- Familiarity with containerization (Docker, Kubernetes) and modern deployment practices.
- Proficiency with multiple persistence technologies, including RDBMS, NoSQL, GraphDBs, and vector/RAG storage solutions.
- Solid understanding of cloud platforms (AWS, Azure, or GCP).
Preferred Qualifications:
- Experience building and deploying backend systems in regulated environments requiring NIST-53 compliance.
- Strong background in AI/LLM system integrations and agentic software development.
- Experience with web scraping technologies and data extraction techniques.
- Proven leadership in architecting enterprise-grade backend and data solutions.
- Experience with data streaming technologies (e.g., Kafka, Kinesis).
- Advanced degree in Computer Science, Data Science, or a related field.
Location: Remote, with a preference for candidates in the Central Time Zone.