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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, generalist AI title, mid-level expectation, and metro location drive high competition.
GenAI engineering skills transfer across industries, though payments/fintech experience is advantageous.
Extensive mandatory GenAI, MLOps, cloud, and deployment skills indicate high technical shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy enterprise-grade AI and Generative AI solutions including LLM applications, Agentic AI systems, and RAG frameworks for business and operational efficiency.
Build scalable AI pipelines, backend services, APIs, and AI agent architectures to automate workflows and enable AI-powered decision-making.
Collaborate with global business and technology stakeholders to identify AI opportunities, ensure compliance with security, privacy, and Responsible AI standards, and drive adoption of AI solutions.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Data Science, or related technical field.
Experience designing, developing, and deploying AI, Generative AI, or ML solutions in production environments with hands-on LLM and Agentic AI system expertise.
Strong Python programming skills and experience with cloud platforms (Azure, AWS), AI/ML frameworks, and large-scale data processing technologies.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Proven experience building and operationalizing complex AI applications including LLMs, Retrieval-Augmented Generation, and orchestration of AI agents with GenAI frameworks like OpenAI, LangChain.
Comfortable working at the intersection of AI engineering and business domain experts to translate requirements into scalable AI solutions in a fast-paced, evolving environment.
Familiar with Responsible AI implementation, including bias monitoring, explainability, and AI safety, and adept at managing AI solution lifecycle with MLOps/LLMOps practices.