As a Full-Stack Software Engineer on the Agentic AI Platform team, you will be instrumental in building both the backend systems and the frontend interfaces that power our sophisticated AI agents. You will tackle challenging technical problems across the stack, implementing robust backend services, APIs, and scalable infrastructure, as well as developing intuitive user interfaces for internal tools, testing environments, or agent interaction components.
You will contribute to the architectural direction, collaborating closely with backend specialists, frontend developers, designers, and AI researchers. This role requires strong software engineering fundamentals across both backend and frontend development, practical experience building scalable systems, and a keen interest or experience in modern AI technologies, especially Large Language Models (LLMs).
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1. Full-Stack Development & Implementation:
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Design, implement, test, and deploy robust backend components for the agentic AI platform (APIs, services, orchestration, data persistence) using languages like Python, Typescript, Java, etc. (Python highly relevant).
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Design, implement, test, and deploy user-facing features and internal tools using modern frontend technologies, including JavaScript, TypeScript, React, HTML, and CSS.
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Develop core libraries, SDKs, and components across the stack to enable efficient development and deployment of AI agents and associated tooling.
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Write high-quality, maintainable, and well-tested code for both backend and frontend systems.
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Implement and improve monitoring, logging, and alerting across the full stack.
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Participate actively in code reviews for both frontend and backend code.
2. Technical Design & Contribution:
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Contribute significantly to technical design and architecture discussions, considering both backend and frontend implications for new features and system improvements.
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Collaborate with principal engineers, product managers, UX/UI designers, and researchers to refine requirements and translate them into effective full-stack technical solutions.
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Evaluate and prototype new technologies, algorithms, and frameworks relevant to agentic AI, platform infrastructure, and frontend development.
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Take ownership of the technical implementation for specific features or components spanning the full stack.
3. Collaboration & Knowledge Sharing:
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Work closely with teammates and cross-functional partners (Product, Design, Research, other Engineering teams) to deliver cohesive user experiences and robust backend capabilities.
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Share knowledge, document designs and processes effectively for both backend and frontend aspects.
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May mentor junior engineers on full-stack development practices.
4. Operational Excellence:
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Troubleshoot and debug complex issues in production environments, potentially spanning frontend, backend, and infrastructure layers.
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Participate in addressing issues across the stack.
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Contribute to improving the scalability, performance, security, usability, and cost-effectiveness of the platform and its interfaces.
What You Should Bring
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Bachelors degree in Computer Science, Engineering, or a related field.
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5+ years of professional full-stack software development experience.
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Strong proficiency in one or more backend programming languages such as Python, Javascript/Typescript or Java (Python highly relevant for the AI domain).
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Strong proficiency in frontend technologies including JavaScript, TypeScript, HTML, CSS, and modern frontend frameworks (specifically React).
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Experience building developer tools or interfaces for complex technical products (e.g., AI/ML tooling, data platforms).
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Hands-on experience with agentic AI concepts/frameworks (e.g., LangChain, LlamaIndex), vector databases (e.g., Pinecone, Weaviate), or RAG techniques.
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Experience in computer science fundamentals (data structures, algorithms, operating systems, networking).
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Experience building, deploying, and operating backend services and APIs in a cloud environment (AWS, GCP, or Azure).
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Experience building and deploying responsive and performant user interfaces.
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Experience with system design and architecture, with the ability to contribute to complex design discussions covering the full stack.
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Interest in or practical experience with AI/ML concepts , particularly working with or integrating Large Language Models (LLMs).
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Experience with software development best practices (testing frameworks for backend and frontend, CI/CD, monitoring, code reviews).
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Strong problem-solving skills and attention to detail.
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Good communication and collaboration skills, including working with designers.
Preferred Qualifications
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Experience building platform or infrastructure-as-a-service components.
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Experience with state management libraries (e.g., Redux, Zustand) and frontend build tools (e.g., Webpack, Vite).
- Experience with MLOps practices and tools.
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Experience with containerization (Docker) and orchestration (Kubernetes).
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Experience with infrastructure-as-code (e.g., Terraform).
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Experience optimizing the performance and scalability of both backend distributed systems and frontend applications.
