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About the Role
Senior backend Python Engineer (AI-Native & Agentic Workflows)
Key Skills for This Role
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Responsibilities
- Job Description:
- Design, implement, and manage high-performance backend systems using Python (FastAPI/Django).
- Architect scalable RESTful and FAST APIs and microservices connecting enterprise data and analytics platforms.
- Build, containerize, and deploy backend applications on AWS using Docker and container orchestration platforms (ECS/EKS).
- Develop and maintain CI/CD pipelines to automate build, test, container image creation, and deployment to AWS (ECS/EKS).
- Ensure APIs are secure, resilient, and optimized for performance and scalability.
- Implement multi-threading and multiprocessing where appropriate for performance optimization.
- Integrate and orchestrate LLM-driven workflows using modern agentic frameworks.
- Utilize AI coding assistants (e.g., Claude Code, Codex, Copilot, Cursor) to enhance development velocity and automation.
- Build scalable AI-driven enterprise intelligence layers including vector-based APIs and retrieval workflows.
- Debug, optimize, and enhance existing services for reliability and performance.
- Implement observability and monitoring for containerized services (logs, metrics, traces) using CloudWatch and/or APM tooling.
- Maintain comprehensive documentation for APIs, infrastructure, and AI-driven workflows.
- Follow best practices for clean code, security, observability, and performance optimization.
- Primary Skills:
- Python: Advanced proficiency in Python 3, including OOP, multithreading, multiprocessing, and modular architecture.
- FastAPI / Django: Strong experience building production-grade APIs.
- REST APIs: Deep understanding of REST principles and microservices design.
- Containers: Strong experience with Docker (Dockerfiles, image optimization, multi-stage builds, container security basics).
- AWS Container Deployments: Proven experience deploying and operating containerized applications on AWS
- AI & Agentic Frameworks: Hands-on experience with LangChain, LangGraph, AutoGen, or similar LLM orchestration frameworks.
- AI-Assisted Development Tools: Experience using tools such as Cursor, Copilot Workspace, Claude Code, Codex, or equivalent.
- Vector & Retrieval Systems: Understanding of vector-based APIs and modern search/retrieval architectures.
- Problem-Solving: Strong analytical and troubleshooting skills.
- Communication: Excellent verbal and written communication skills.
- Job Description: - Design, implement, and manage high-performance backend systems using Python (FastAPI/Django). - Architect scalable RESTful and FAST APIs and microservices connecting enterprise data and analytics platforms. - Build, containerize, and deploy backend applications on AWS using Docker and container orchestration platforms (ECS/EKS). - Develop and maintain CI/CD pipelines to automate build, test, container image creation, and deployment to AWS (ECS/EKS). - Ensure APIs are secure, resilient, and optimized for performance and scalability. - Implement multi-threading and multiprocessing where appropriate for performance optimization. - Integrate and orchestrate LLM-driven workflows using modern agentic frameworks. - Utilize AI coding assistants (e.g., Claude Code, Codex, Copilot, Cursor) to enhance development velocity and automation. - Build scalable AI-driven enterprise intelligence layers including vector-based APIs and retrieval workflows. - Debug, optimize, and enhance existing services for reliability and performance. - Implement observability and monitoring for containerized services (logs, metrics, traces) using CloudWatch and/or APM tooling. - Maintain comprehensive documentation for APIs, infrastructure, and AI-driven workflows. - Follow best practices for clean code, security, observability, and performance optimization. Primary Skills: - Python: Advanced proficiency in Python 3, including OOP, multithreading, multiprocessing, and modular architecture. - FastAPI / Django: Strong experience building production-grade APIs. - REST APIs: Deep understanding of REST principles and microservices design. - Containers: Strong experience with Docker (Dockerfiles, image optimization, multi-stage builds, container security basics). - AWS Container Deployments: Proven experience deploying and operating containerized applications on AWS - AI & Agentic Frameworks: Hands-on experience with LangChain, LangGraph, AutoGen, or similar LLM orchestration frameworks. - AI-Assisted Development Tools: Experience using tools such as Cursor, Copilot Workspace, Claude Code, Codex, or equivalent. - Vector & Retrieval Systems: Understanding of vector-based APIs and modern search/retrieval architectures. - Problem-Solving: Strong analytical and troubleshooting skills. - Communication: Excellent verbal and written communication skills.
Qualifications
- 5–7 years of experience in software development with strong focus on Python backend architecture.
- Hands-on experience containerizing applications and deploying them to AWS using ECS/EKS in production environments.
- Exposure to generative AI integration in production systems.
- Experience working in fast-paced delivery environments supporting continuous deployment cycles.
- Experience working in distributed or dual-shore delivery models is preferred.
- Strong ownership mindset and architectural thinking capability.
- - 5–7 years of experience in software development with strong focus on Python backend architecture. - Hands-on experience containerizing applications and deploying them to AWS using ECS/EKS in production environments. - Exposure to generative AI integration in production systems. - Experience working in fast-paced delivery environments supporting continuous deployment cycles. - Experience working in distributed or dual-shore delivery models is preferred. - Strong ownership mindset and architectural thinking capability.
About EXL
EXL is a global data and AI company that provides analytics, digital operations, and industry-specific services to enterprises in insurance, healthcare, banking, retail, media, and energy.
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