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Mid-level experience and metro location increase competition despite niche GenAI skill requirements.
Specialized GenAI, LLM, RLHF, and vector DB expertise limits easy transfer across non-AI roles.
Multiple mandatory filters (5-7 years, 2+ years architecture, LLMs, vector DBs, Azure) increase strictness.
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Own end-to-end architecture and technical design for AI-driven product and client projects, ensuring scalable, secure, and cost-efficient solutions.
Develop prototypes and proof-of-concepts to validate technical approaches and establish AI engineering standards across teams.
Lead architecture reviews, technical debt management, and integration architecture for internal/external systems ensuring adherence to engineering principles.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.
5-7 years of software engineering experience with at least 2 years in architecture or technical leadership roles.
Hands-on experience with LLMs (OpenAI, Claude, Gemini, Llama) and GenAI frameworks (LangChain, LlamaIndex).
Strong full stack development skills (Python, JavaScript/TypeScript) with cloud-native deployment experience, preferably Azure.
Experienced in designing API-first, composable service architectures and integration patterns for AI applications.
Proven ability to translate business requirements into technical blueprints and make architectural decisions under ambiguity.
Comfortable leading teams technically while balancing delivery speed and architecture quality in agile/hyper-agile environments.