Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 employer, metro location, and desirable GenAI skills create moderate competition.
Highly specialized GenAI and LLMOps expertise required makes background fit sensitivity high.
Extensive mandatory GenAI platform, LLMOps, cloud, and Python/Kubernetes requirements create high shortlisting strictness.
Lead and deliver moderately complex AI and software engineering initiatives including design, development, and deployment of AI-enabled applications and services.
Design and build scalable, secure AI platforms leveraging GenAI technologies and frameworks; guide integrations with cloud AI platforms and enterprise container environments.
Collaborate across teams to develop reusable AI components, agentic workflows, observability tooling, and ensure compliance with enterprise and regulatory standards.
Experience Required: Not explicitly mentioned in the JD, but senior-level role indicates significant experience with GenAI platforms and software engineering.
Proficiency in Python and frameworks like FastAPI, Flask, MCP; experience with React, TypeScript for frontend development.
Strong knowledge of AI platforms and orchestration frameworks (LangChain, LangGraph, AutoGen, MCP) and cloud AI services (Azure OpenAI, AWS Bedrock, Google Vertex AI).
Experience with Kubernetes, microservices architecture, REST API development, vector/graph databases, and AI observability tools (Arize, Splunk).
Experienced in architecting and scaling enterprise AI/GenAI systems using agentic AI frameworks and model orchestration solutions.
Capable of leading moderately complex technical projects and mentoring less experienced engineers within regulated enterprise environments.
Strong cross-functional collaborator who can integrate AI solutions with secure, scalable cloud-native infrastructure and CI/CD automation pipelines.