Roles and Responsibilities :
Design and develop large language models using Python, focusing on agentic AI capabilities.
Collaborate with cross-functional teams to integrate generative AI solutions into existing systems.
Develop and maintain complex neural networks for natural language processing tasks such as text classification, sentiment analysis, and machine translation.
Conduct research on cutting-edge techniques in deep learning and neural networks to stay up-to-date with industry trends.

Job Requirements :
1. Robust experience in enterprise solution architecture and application modernization.
Hands-on understanding of LLMs, RAG, embeddings/vector databases, tool/function calling, agent orchestration, multi-agent workflows, MCP, prompt/context engineering, AI evaluation, guardrails, and human-in-the-loop patterns
Strong hands-on experience with AWS/ Google/ Azure cloud architecture and services.
Experience with contemporary frontend technologies such as React, Next.js, Angular, JavaScript, and TypeScript.
Robust backend experience with one or more of .NET/C#, Python, Node.js, Java, with the ability to understand and review solutions across different technology stacks.
Strong knowledge of REST APIs, OpenAPI/Swagger,



API-first architecture, and enterprise integration patterns.
Experience with OAuth 2.0, OIDC, JWT, SSO, API security, IAM, and secrets management.
Experience with Docker, Kubernetes, ECS/EKS, serverless/Lambda, and cloud-native architectures.
Experience with relational databases such as PostgreSQL, SQL Server, AWS RDS/Aurora, including data integration and migration patterns.
Hands-on experience with Terraform, Pulumi, CloudFormation, or equivalent Infrastructure as Code technologies.
Robust understanding of CI/CD pipelines, GitHub Actions/Azure DevOps, branching strategies, and automated quality gates.
Experience with observability and monitoring platforms such as Datadog and AWS CloudWatch.
Understanding of microservices, modular architectures, event-driven architecture, distributed systems, and enterprise integration patterns.
Working knowledge of GenAI/LLMs, RAG, vector databases, AI agents, prompt engineering, and AI-enabled application development.
Strong experience using AI coding assistants for code generation, repository analysis, modernization, test generation, debugging, and documentation.

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📌 Gen Ai Architect Hyderabad
🏢 Virtusa
📍 Hyderabad