Description :

Job Summary :

We are seeking a highly skilled and motivated Senior Full-Stack Engineer with a strong foundation in backend development to join our core team, dedicated to pioneering the next generation of intelligent systems.

This role is at the intersection of scalable backend architecture and cutting-edge agentic AI innovation.

The engineer will be responsible for designing, building, and maintaining the secure, performant, and intelligent infrastructure required to support autonomous, agent-based systems, specifically enabling complex Agent-to-Agent communication and decision-making capabilities that extend beyond conventional Large Language Model (LLM) applications.

Key Responsibilities :

Backend and AI Systems Development :

- Architect and develop highly scalable and secure backend systems primarily utilizing Python and modern frameworks such as Django or FastAPI.

- Design, implement, and maintain robust RESTful APIs and microservices to facilitate internal and external system interactions, focusing on performance and reliability.

- Drive the core technical implementation of agentic systems using state-of-the-art frameworks like LangGraph and CrewAI, enabling complex workflows, reasoning, and autonomous execution.

- Implement and manage the Model Context Protocol (MCP) or similar standards to govern and optimize agent-to-agent communication and autonomous decision flows.

Data Management and Infrastructure :

- Model, manage, and optimize complex data structures within relational databases (e.g., PostgreSQL, MySQL), leveraging advanced features of ORMs like Django ORM or SQLAlchemy.

- Design and build containerized services using Docker, and manage deployment, monitoring, and debugging processes within the Linux environment.

- Implement and manage comprehensive CI/CD pipelines (e.g., GitLab CI, GitHub Actions) to ensure automated testing, secure deployment, and rapid iteration.

Cross-Functional and Quality Assurance :

- Seamlessly integrate advanced AI functionalities and features by interfacing with various LLMs and external proprietary AI APIs.

- Collaborate effectively with frontend counterparts, contributing to user-facing features using JavaScript/TypeScript and modern frameworks (e.g., Svelte, React, or Angular) as needed.

- Implement rigorous unit testing, integration testing, and end-to-end testing across all services to maintain high code quality and functional accuracy.

- Enforce stringent standards for security, performance optimization, and compliance (e.g., data privacy, access controls) across the entire application stack.

Required Qualifications :

Experience : 4- 7 years of relevant, hands-on software development experience, with a significant emphasis on backend development and system architecture.

Programming and Frameworks :

- Expert-level proficiency in Python for developing enterprise-grade, scalable services.

- Proven experience with major Python web frameworks : Django and/or FastAPI.

API and Data Layer :

- Expertise in REST API design and development, including versioning, documentation (e.g., OpenAPI/Swagger), and optimization.

- Deep, practical experience with SQL databases (PostgreSQL/MySQL) and utilizing ORMs (Django ORM, SQLAlchemy) for complex data modeling and querying.

DevOps and Tooling :

- Proficiency in containerization technologies (Docker) and experience deploying and managing applications on Linux.

- Solid practical knowledge of Git workflows and experience implementing/maintaining CI/CD pipelines.

Frontend Acumen :

- Basic to intermediate proficiency in JavaScript/TypeScript and familiarity with at least one modern frontend framework (Svelte, React, or Angular).

Preferred Skills :

- Agentic AI Frameworks : Direct, hands-on experience developing sophisticated applications using LangGraph or CrewAI.

- LLM Integration : Experience working directly with LLM APIs (e.g., OpenAI, Anthropic, OSS models) and fine-tuning model outputs for specific tasks.

- Cloud Platforms : Experience with major cloud providers (AWS, Azure, or GCP) including familiarity with managed database services and serverless/container orchestration services (e.g., ECS, Kubernetes).

- Observability : Practical experience implementing and utilizing observability tools such as Prometheus, Grafana, or Datadog for monitoring system performance and health.

- Messaging : Experience with asynchronous communication and messaging queues (e.g., Kafka, RabbitMQ) for building highly decoupled, scalable architectures