Technical Architect at E-Commerce Product Based Company · Bengaluru (Bangalore) · 8 - 15 years · ₹15L - ₹30L / yr · Posted 20 Nov 2019
Role and Responsibilities
- Build a low latency serving layer that powers DataWeave's Dashboards, Reports, and Analytics functionality
- Build robust RESTful APIs that serve data and insights to DataWeave and other products
- Design user interaction workflows on our products and integrating them with data APIs
- Help stabilize and scale our existing systems. Help design the next generation systems.
- Scale our back end data and analytics pipeline to handle increasingly large amounts of data.
- Work closely with the Head of Products and UX designers to understand the product vision and design philosophy
- Lead/be a part of all major tech decisions. Bring in best practices. Mentor younger team members and interns.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope.
Skills and Requirements
- 8- 15 years of experience building and scaling APIs and web applications.
- Experience building and managing large scale data/analytics systems.
- Have a strong grasp of CS fundamentals and excellent problem solving abilities. Have a good understanding of software design principles and architectural best practices.
- Be passionate about writing code and have experience coding in multiple languages, including at least one scripting language, preferably Python.
- Be able to argue convincingly why feature X of language Y rocks/sucks, or why a certain design decision is right/wrong, and so on.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- Have experience working with multiple storage and indexing technologies such as MySQL, Redis, MongoDB, Cassandra, Elastic.
- Good knowledge (including internals) of messaging systems such as Kafka and RabbitMQ.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Exposure to one or more centralized logging, monitoring, and instrumentation tools, such as Kibana, Graylog, StatsD, Datadog etc.
- Working knowledge of building websites and apps. Good understanding of integration complexities and dependencies.
- Working knowledge linux server administration as well as the AWS ecosystem is desirable.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.

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The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems.
Responsibilities
- Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms
- Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning
- Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection
- Deploy, maintain and monitor containerized ML workloads
- Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows
- Implement AI-driven data validation, schema and concept drift detection and metadata management.
- Establish governance frameworks for AI systems, including bias detection, explainability, and auditability
- Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention
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- Monitor model KPIs (accuracy, precision, recall, latency, calibration)
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- Bachelor’s degree in computer science, Data Science, Information Systems, or a related field
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Educational Qualification
Graduates or Undergraduate
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* Explore, Implementation & usage of code coverage tools
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* Curiosity & appetite to learn: Would have acquired detailed understanding of the overall system. Number of secondary code reviews performed Always discussing alternatives for the existing automation tech stack to keep it current.
* Mentoring: Demonstrated an ability to mentor junior members of the team, and leading thoughtprovoking technical conversations, be it pertaining to the current tech stack or new emerging technologies.
* Good to have: Knowledge of CI/CD & Agile process.
* Good to have: Performance/Load testing experience
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* Must have knowledge of Mobile Automation Testing (Appium or alternatives)
* Excellent communications and technical presentation skills
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