Quick overview
Job description
Responsibilities:
- Design and implement backend services and APIs to power scalable, secure, and efficient agentic solutions.
- Develop and optimize data pipelines for ingestion, transformation, and real-time processing of large datasets.
- Development distributed systems leveraging cloud platforms (Azure, AWS, or GCP) and containerization (Docker/Kubernetes) for high availability and fault tolerance.
- Integrate backend logic with front-end frameworks (React, Next.js, Typescript) to deliver seamless user experiences.
- Implement security best practices across authentication, authorization, and data protection layers.
- Collaborate with cross-functional teams including product management, design, and QA to align technical solutions with business goals.
- Conduct code reviews and enforce standards for performance, reliability, and security.
- Continuously research and integrate emerging technologies such as LLM orchestration, multi-agent systems, and knowledge graphs.
- Document architecture and technical decisions for transparency, scalability, and maintainability.
Professional Qualifications:
- Bachelor’s degree in computer science, AI/ML, Data Engineering, or related field.
- Strong proficiency in coding languages (e.g., C#, Java, Python, or C++).
- Passion for solving customer problems.
- Hands-on experience with data pipelines, cloud platforms (Azure, AWS, or GCP), and containerization (Docker/Kubernetes).
- Proven ability to work in agile environments, managing ambiguity and delivering impactful outcomes.
Preferred Qualifications:
- Experience in building AI-driven applications or distributed systems.
- Hands-on experience developing full-stack solutions (React, Next.js, Typescript, Node.js)
- Experience with nsjail, Firecracker and MS Orleans preferred.
- Experience with vector databases, semantic search, and prompt engineering.
- Knowledge of reinforcement learning, planning algorithms, or multi-agent coordination.
- Familiarity with LLM frameworks, agent orchestration, and knowledge representation techniques.
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