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Specialist - AI Engineering

  • Source: LinkedIn
  • Workowon
  • On-site
  • Hyderabad
  • Full-Time
  • Senior

Job Description

About The Job MSD is seeking an AI Engineer to drive the end-to-end development of GenAI applications, including prompt engineering, fine-tuning, RAG pipelines, and LLM-based workflows, ensuring high standards of performance and scalability.

Key Responsibilities

  • Implement Agentic AI systems leveraging frameworks such as LangChain, Google ADK, Strands, and Semantic Kernel.
  • Apply advanced prompt engineering techniques to improve accuracy and robustness of LLM systems.
  • Build multimodal AI solutions, integrating text with images or structured data to support enterprise use cases.
  • Apply harness engineering practices to systematically design, test, and evaluate AI workflows.
  • Develop reusable agent tooling and integrations, including Model Context Protocol and Agent-to-Agent communication.
  • Collaborate with stakeholders to translate business problems into scalable GenAI-driven solutions.
  • Leverage modern AI developer tooling such as Claude CLI, GitHub Copilot, and Vertex AI.
  • Support deployment and operationalization of AI solutions using AWS and GCP clouds.

Requirements Requirements

  • Masters in a relevant quantitative, applied field such as Statistics, Econometrics, Computer Science, Mathematics, or Engineering.
  • Minimum of 5 years of work experience in the end-to-end lifecycle of ML model development and deployment into production.
  • Expertise in RAG architectures, including embedding generation, retrieval optimization, and context management.
  • Experience in prompt engineering techniques and AgentOps practices.
  • Strong Python programming skills with experience in tooling and function-calling.
  • Solid expertise in NLP and text processing.

Preferred Qualifications

  • Exposure to multimodal AI systems involving text, vision, or structured data fusion.
  • Familiarity with LLM evaluation techniques, synthetic test generation, and prompt regression testing.
  • Hands-on experience with TensorFlow or PyTorch for custom model development.
  • Exposure to LLMOps/MLOps practices for deployment and monitoring.

Skills PythonRAG ArchitecturesLangChainNLPMachine LearningPyTorch

Benefits

  • Wellness programs
  • Visa / relocation support

Skills

  • LangChain
  • claude-by-anthropic
  • Github
  • gitHub-copilot
  • vertex
  • amazon-web-services
  • google-cloud-platform
  • Python
  • Tensorflow
  • PyTorch

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