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Tier-1 brand plus metro location raise applicant density, but AI specialization narrows the qualified pool.
AI and cloud-focused engineering skills are transferable across industries but require domain-specific ML expertise.
Many mandatory technical skills and domain expertise required, making automated shortlisting stringent.
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Design, develop, test, and maintain micro-services based software solutions handling structured and unstructured data, including ML/AI algorithms.
Responsible for code quality through writing, testing, refactoring, automated testing, deployment, and code reviews across geo-distributed teams.
Collaborate with multiple teams and stakeholders to deliver scalable, cloud-based software products using APIs and telemetry data.
Bachelor's degree or equivalent in Computer Science, Engineering or related field.
Seasoned experience in software development including micro-services, RESTful APIs, cloud architecture (AWS, GCP, Azure), and data stores (SQL, no-SQL like Elasticsearch, MongoDB, Cassandra).
Expertise in programming languages such as C/C++, C#, Java, JavaScript, Python, Node.js and knowledge of container runtime (Kubernetes, Docker).
Work Experience Required: Seasoned experience with geo-distributed teams, Agile/Lean methodologies, CI/CD tools, software delivery lifecycle, and working with large data sets applying ML/AI algorithms.
Experienced software engineer capable of architecting and developing scalable micro-services in cloud environments with automated testing and CI/CD.
Able to work across multiple teams and manage stakeholder requirements in fast-paced, dynamic environments.
Strong technical expertise in full software lifecycle, distributed systems, and advanced data handling including ML/AI algorithm deployment.