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Amazon Web Services (AWS)Backend Engineer III – Senior Python Developer (LLM & AI)
Location: Gurgaon, India
Positions: 1
Experience: 6 to 9 Years
Gurgaon Hybrid
About the Role
We are seeking an experienced Backend Engineer III / Senior Python Developer to join our AI engineering team and play a critical role in building scalable, secure, and high-performance backend platforms for LLM and AI-driven applications. You will work as a hands-on individual contributor while collaborating closely with Machine Learning Engineers, Data Scientists, Product Managers, and Cloud/DevOps teams to deliver innovative, production-grade AI solutions.
Key Responsibilities
- Design, develop, and maintain scalable backend systems and services using Python to support LLM and AI-based applications
- Build and maintain RESTful APIs and microservices that serve machine learning models and AI components
- Write clean, modular, efficient, and testable code following industry best practices and coding standards
- Participate actively in code reviews, ensuring high quality, security, and maintainability of the codebase
- Debug, profile, and optimize applications to improve performance, reliability, and scalability
- Identify and resolve performance bottlenecks in AI/ML pipelines and backend services
- Collaborate with ML engineers, data scientists, and product teams to translate business and technical requirements into robust backend solutions
- Mentor and support junior developers, promoting a culture of technical excellence and continuous learning
- Design and implement CI/CD pipelines and automate deployment workflows to ensure consistent and reliable releases
- Stay up to date with emerging trends in Python, cloud-native development, and LLM/AI engineering practices and apply them to improve systems and processes
Required Skills & Experience
- 6 to 9 years of strong hands-on experience in Python development
- Solid understanding of Python software design, architecture patterns, and testing best practices
- Proven experience working on AI, Machine Learning, or LLM-based projects
- Strong experience in building and consuming RESTful APIs and microservices architectures
- Hands-on experience with FastAPI, Flask, or similar model-serving frameworks
- Strong debugging, performance profiling, and optimization skills
- Experience with CI/CD tools and workflows (e.g., GitHub Actions, Azure DevOps, Jenkins, etc.)
- Working knowledge of Docker and Kubernetes is a strong plus
- Excellent analytical, problem-solving, and communication skills
- Ability to work independently in a fast-paced, evolving AI/ML environment while mentoring junior team members
Education & Certifications
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
- AWS or other relevant cloud certifications are preferred but not mandatory
Why Join Us?
- Work on cutting-edge AI and LLM platforms
- Collaborate with top-tier engineering and data science teams
- Opportunity to influence system architecture and technical direction
- Competitive compensation and career growth opportunities
We are looking for a skilled DevOps Engineer with strong expertise in Microsoft Azure and Pulumi to join our growing engineering team. The ideal candidate will be responsible for designing, implementing, and maintaining scalable cloud infrastructure and CI/CD pipelines. This role requires hands-on experience with Infrastructure as Code (IaC), automation, and cloud-native DevOps practices while collaborating closely with development and platform teams.
The candidate must be comfortable working in a U.S. time zone overlap, ensuring smooth collaboration with onshore teams.
Key Responsibilities
- Design, implement, and maintain cloud infrastructure on Microsoft Azure using modern DevOps practices.
- Develop and manage Infrastructure as Code (IaC) using Pulumi to automate infrastructure provisioning and management.
- Build, maintain, and optimize CI/CD pipelines to support reliable and frequent deployments.
- Monitor, troubleshoot, and improve cloud infrastructure performance, availability, and security.
- Collaborate with development teams to improve deployment processes and application reliability.
- Implement automation and configuration management to streamline operations.
- Manage containerized applications and orchestration platforms when applicable.
- Ensure adherence to cloud security best practices, governance, and compliance standards.
- Support production environments and resolve infrastructure-related issues in a timely manner.
- Maintain documentation for infrastructure architecture, deployment pipelines, and operational procedures.
Required Skills & Experience
- 4–7 years of experience in DevOps, Cloud Engineering, or related roles.
- Strong hands-on experience with Microsoft Azure cloud services.
- Proven experience using Pulumi for Infrastructure as Code (must-have).
- Experience building and managing CI/CD pipelines using tools like Azure DevOps, GitHub Actions, Jenkins, or similar.
- Strong experience with containerization technologies (Docker, Kubernetes).
- Proficiency with scripting languages such as Python, Bash, or PowerShell.
- Experience with monitoring and logging tools.
- Strong understanding of cloud networking, security, and identity management.
- Experience with Git-based version control systems.
Preferred Qualifications
- Experience with Kubernetes in Azure (AKS).
- Familiarity with observability tools such as Prometheus, Grafana, or similar.
- Experience with cloud cost optimization and performance tuning.
- Knowledge of DevSecOps practices and security automation.
- Azure certifications such as Azure DevOps Engineer Expert or Azure Administrator.
Amazon Web Services (AWS)
NodeJS (Node.js)
React.jsJob Title: Principal Architect / Scalability Lead (AWS)
📍 Location: Gurgaon (Hybrid)
🕒 Employment Type: Full-Time
Role Overview
We are seeking a Principal Architect / Scalability Lead with deep expertise in AWS and large-scale distributed systems to architect and scale cloud-native products from MVP to enterprise scale.
This role demands a senior technical leader who has proven experience designing systems that handle high throughput, large concurrent workloads, and enterprise-grade reliability, while ensuring exceptional end-user experience.
You will work closely with Product, Data Engineering, AI/ML, and Backend teams to define architecture standards, scalability roadmaps, and engineering best practices.
Key Responsibilities
🏗 Architecture & Scalability Leadership
- Architect highly scalable, resilient, and high-performance cloud-native systems on AWS.
- Design distributed systems capable of supporting 100K+ concurrent users.
- Lead architecture evolution from MVP to enterprise-grade deployment.
- Translate business and consumer requirements into robust technical architecture.
- Drive scalability planning, capacity modeling, and performance engineering.
🔄 End-to-End Ownership
- Own full SDLC visibility from discovery and design to release, monitoring, and optimization.
- Establish best practices for:
- Microservices architecture
- Distributed systems design
- Observability & monitoring
- DevSecOps & CI/CD
- Ensure system uptime, fault tolerance, and cost efficiency.
☁ AWS Cloud & Infrastructure
- Design and implement scalable systems using AWS services.
- Lead containerization and orchestration using Docker and Kubernetes (EKS).
- Architect secure, automated CI/CD pipelines.
- Drive cloud cost optimization and infrastructure efficiency.
📈 Performance & Reliability Engineering
- Define and enforce SLAs, SLOs, and reliability metrics.
- Lead performance testing, load testing, and scalability validation.
- Implement monitoring, alerting, and observability frameworks.
- Design fault-tolerant and highly available systems.
🧠 Backend, Data & AI Collaboration
- Provide architectural guidance for:
- Backend services using Node.js and Python
- Frontend platforms using React / Next.js
- Data platforms using Snowflake
- Collaborate with Data Engineering and AI/ML teams on data-intensive and AI-driven systems.
- Design architectures supporting asynchronous processing, caching, and event-driven workflows.
👥 Leadership & Governance
- Mentor senior engineers and guide architecture best practices.
- Lead architecture governance and design reviews.
- Influence senior stakeholders with data-driven technical decisions.
- Drive cross-functional alignment across Product, Engineering, Data, and AI teams.
Required Qualifications
- 8–15 years of experience in software engineering.
- Proven experience scaling distributed systems handling 100K+ users or high-throughput workloads.
- Deep hands-on expertise in AWS cloud architecture.
- Strong experience with Docker, Kubernetes, and container orchestration.
- Expertise in microservices, caching strategies, asynchronous processing, and distributed systems.
- Strong understanding of performance engineering and reliability frameworks.
- Experience building enterprise-grade systems for large-scale organizations.
Preferred Skills
- Experience with event-driven architectures (Kafka, SQS, SNS, etc.).
- Knowledge of database scalability and data warehousing (Snowflake).
- Exposure to Data Engineering and AI/ML platforms.
- Strong stakeholder communication and strategic thinking skil
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