Bangalore, Karnataka, India
Information Technology
Full-Time
Speed Engineering Solutions
Overview
Key Responsibilities:
- Contribute to the development of microservices architecture, focusing on data ingestion, complex backend services, and high-velocity data applications.
- Design and implement scalable backend services using AWS cloud technologies.
- Develop, deploy, and optimize ChatGPT-based generative AI agents tailored for various applications including conversational interfaces, data analysis, and automation.
- Microservices Architecture: Architect and implement microservices with independently deployable modules to ensure improved fault isolation, granular scalability, and facilitated continuous delivery.
- Utilize Docker and Kubernetes for containerization and orchestration of microservices.
- Implement API gateways and service meshes (e.g., Istio) for managing internal communication, load balancing, and security policies of microservices.
- Data-Driven Solutions: Build sophisticated data analytics platforms capable of processing and analyzing large datasets in real-time.
- Utilize streaming technologies like Apache Kafka or AWS Kinesis for real-time data ingestion and processing.
- Implement ETL pipelines using AWS Glue, AWS Lambda, or similar technologies.
- Collaborate: Work closely with cross-functional teams, including frontend developers, data scientists, and DevOps engineers, to deliver comprehensive solutions.
- REST/GraphQL Services: Design and implement robust APIs using REST and GraphQL standards.
- Implement GraphQL servers using Apollo or similar frameworks.
- Utilize RESTful API principles for efficient and scalable endpoint design.
- Database Management: Work with SQL and NoSQL databases to ensure efficient and secure data storage, retrieval, and analysis.
- Design and optimize database schemas for performance and scalability.
- Implement data caching strategies using Redis or Memcached.
- Design Patterns and Best Practices: Uphold and advocate for software design patterns and coding standards to maintain high-quality codebases.
- Implement patterns such as Singleton, Factory, Observer, Strategy, and Circuit Breaker to ensure code robustness and maintainability.
- Project Versatility: Flexibly adapt to work on various projects as they arise, with current priorities on IoT, GenAI, and cloud data platforms.
Skills and Experience Required:
- Experience: 5+ Years of experience as a Full Stack Engineer with significant experience in backend development using AWS, NodeJS, and Python.
- Education: Bachelor’s or master’s degree in computer science engineering, or a related field.
- Technical Skills:
- AWS Services: EC2, Lambda, S3, CloudFormation, ECS, RDS, DynamoDB, and other core AWS services.
- Programming Languages: Proficient in NodeJS, Python, and Django.
- Microservices Architecture: Experience in designing and implementing microservices.
- API Development: Strong understanding of REST and GraphQL APIs.
- Database Proficiency: Experience with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases.
- Design Patterns: Familiarity with software design patterns and best practices.
- Additional Competencies:
- IoT Integration: Experience with IoT platforms, data ingestion techniques, and communication protocols (e.g., MQTT, AMQP).
- GenAI: Experience with developing AI models, specifically ChatGPT or similar technologies.
- Familiarity with OpenAI API and fine-tuning GPT models.
- Experience in deploying and scaling AI models in production environments.
- Data Analytics: Strong background in building and optimizing data analytics platforms.
- Proficient with big data technologies (e.g., Hadoop, Spark) and BI tools (e.g., Tableau, PowerBI).
- Collaboration: Strong communication skills and experience working in agile environments.
- Adaptability: Ability to quickly learn new technologies and thrive in a fast-paced, dynamic environment.
- Certifications: AWS Certified Solutions Architect, AWS Certified Developer, or similar certifications.
- Experience with ML/AI: Knowledge or experience in machine learning and AI technologies beyond GenAI.
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