Back
Tier-1 brand and Bangalore increase applicant volume, but senior generative-AI specialization reduces qualified applicant density.
Generative-AI and LLM-specific expertise creates strong domain bias for candidate backgrounds.
Multiple mandatory senior-level AI, LLM, RAG, cloud, and Kubernetes requirements enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain enterprise-grade Generative AI applications leveraging LLMs and RAG with vector databases.
Integrate and optimize foundation models from providers like OpenAI, Anthropic, and Google Gemini, ensuring scalability, latency optimization, and cost efficiency.
Collaborate cross-functionally translating business requirements into secure, high-performing AI solutions; contribute to technical design, architecture, and mentor junior engineers.
Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or related field.
8+ years of software engineering experience including hands-on work with Generative AI technologies.
Proficiency in Python, SQL, experience with LLMs, RAG, vector databases, AI orchestration frameworks (e.g., LangChain, LlamaIndex).
Experience developing REST APIs, microservices, Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).
Experienced in building and optimizing large-scale AI-powered applications in enterprise environments with modern cloud-native practices.
Skilled in integrating multiple AI models and frameworks, with emphasis on Generative AI and RAG engineering.
Capable of leading architectural decisions and mentoring engineers, operating effectively in cross-functional technical teams.