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Tier-1 brand, metro locations, popular mid-level AI role, and 3+ years requirement attract strong applicant density.
Role requires specialized GenAI, LLM, agent frameworks and AI safety skills, limiting cross-industry transferability.
Explicit 3+ years plus mandatory cloud, LLM/agentic frameworks, Kubernetes, and security/CI-CD requirements increase filtering rigor.
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Design, develop, and deliver scalable, maintainable, and high-quality AI/ML software solutions, including agentic AI and LLM-powered applications.
Collaborate cross-functionally with product managers, designers, engineers, and business stakeholders to ensure alignment with business objectives and smooth integration.
Lead or support teams in adopting secure coding practices, testing, and risk management, while influencing technical standards and decision-making within the AI engineering domain.
Bachelor's degree or above in Computer Science, Engineering, Mathematics, or related field.
Minimum 3 years of software engineering experience developing cloud-scale applications on AWS, Azure, or GCP.
Proficiency in Python (preferred) or Java/Go including experience with REST APIs and async frameworks.
Hands-on experience with GenAI/LLM systems, agentic AI frameworks (Strands, LangGraph, or Google ADK), AWS AI services (e.g., Bedrock, SageMaker), Docker, Kubernetes, and CI/CD pipelines.
Experienced in building and deploying AI-powered applications at scale within enterprise cloud environments, especially leveraging GenAI/LLM and agentic AI frameworks.
Able to lead or coordinate engineering teams and drive technical quality including secure coding, testing, and risk controls within AI software projects.
Familiar with AI safety/security concepts, observability tools, infrastructure-as-code practices, and integration of AI tech in regulated domains such as banking.