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Specialist, Software Engineering, Full-Stack, GenAI and Agentic AI

MSD
Hyderabad, IND
Full-time
Hybrid
Discovered 1 weeks ago
Full-stack software engineeringPythonTypeScript or Node.js, Java, or .NETReact, Angular, JavaScript, HTML, and CSSLarge Language Models (LLMs)Prompt engineering
Free

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Full-stack software engineeringPythonTypeScript or Node.js, Java, or .NET
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Role Overview

Full-stack software engineering role based at the Hyderabad Tech Center.

Design, develop, deploy, and support secure, scalable solutions across user interface, API, data, cloud, and AI layers.

Contribute to GenAI and agentic AI solutions using LLMs, RAG, AI agents, enterprise integrations, and cloud-native technologies.

Workplace

  • Hybrid working model with 3 days onsite and 2 days remote.
  • Candidates are expected to reside within commuting distance of the Hyderabad office.

Core Responsibilities

  • Develop full-stack applications, responsive interfaces, secure APIs, microservices, backend services, and enterprise integrations.
  • Build and optimize RAG pipelines and agentic workflows, including evaluation, orchestration, memory, and human-in-the-loop interactions.
  • Deploy, monitor, test, secure, and support applications and production AI systems on cloud platforms.
  • Participate in Agile product delivery, solution design, sprint planning, and continuous improvement.

Required Qualifications

  • Bachelor's degree in Information Technology, Computer Science, or a related field.
  • 3–7 years of hands-on full-stack development experience.
  • Experience building cloud-native applications and deploying solutions into production environments.
  • Strong Python skills plus at least one additional stack such as TypeScript/Node.js, Java, or .NET.

Primary Skills

  • Full-stack engineering across frontend, backend, APIs, integrations, databases, cloud-native architectures, and enterprise applications.
  • LLMs, prompt engineering, RAG, embeddings, semantic search, AI-powered applications, and agentic workflows.
  • Cloud platforms, microservices, containers, serverless architectures, managed services, DevSecOps, Git, CI/CD, Infrastructure as Code, and automated testing.
  • LLMOps practices including AI monitoring, model evaluation, prompt management, versioning, and production observability.

Secondary Skills

  • AWS Bedrock, Azure OpenAI, Azure AI Foundry, Amazon SageMaker, or similar AI platforms are advantageous.
  • Vector databases, search technologies, GenAI frameworks, Docker, Kubernetes, and platform engineering experience are advantageous.
  • AWS, GCP, or Azure certifications and healthcare or life sciences experience are advantageous.

Employment Details

  • Employee status is listed as regular.
  • No travel is required.

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