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Mid-level LLM/full-stack AI role with broad skill requirements yields moderate applicant competition.
Role's LLM and AI-specific requirements reduce cross-industry transferability moderately.
Explicit 3+ years, required LLM experience, cloud and security needs drive strict shortlisting.
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Design, develop, and maintain AI-enabled applications integrating LLMs, RAG pipelines, and agentic workflows with secure, observable, production-grade standards.
Implement full-stack solutions including backend services, APIs, user interfaces, cloud-native deployment assets, and secure enterprise connectors.
Ensure operational readiness, quality engineering, secure engineering, and Agile delivery including logging, telemetry, testing, code reviews, and documentation.
3 to 5+ years software engineering experience, including at least 1 year in AI/ML or LLM-integrated applications.
Proficient in Python or equivalent language for enterprise AI development.
Experience with REST APIs, asynchronous processing, authentication, CI/CD, and deployments on major cloud platforms.
Practical experience with LLM SDKs/APIs (prompt orchestration, RAG, tool calling), secure coding, privacy, and responsible AI controls.
Experienced full-stack AI developer comfortable building and integrating complex LLM-driven workflows and enterprise-grade solutions.
Skilled in managing end-to-end AI application lifecycle in fast-paced Agile environments with iterative evaluation and stakeholder feedback.
Familiar with secure coding practices, operational readiness, and compliance requirements, especially in regulated domains like financial services.