Senior Specialist - AI Engineering

About The Job MSD is seeking a Senior/Principal AI Engineer to drive the end-to-end development of GenAI applications, including prompt engineering, fine-tuning, RAG pipelines, and LLM-based workflows. You will provide technical leadership, mentor teams, and translate complex AI capabilities into impactful business solutions.

Key Responsibilities

• Design and implement Agentic AI systems leveraging frameworks such as LangChain, Google ADK, Strands, and Semantic Kernel, enabling multi-step reasoning and task orchestration.
• Develop and operationalize multi-agent systems, incorporating patterns such as planning, tool usage, memory, and iterative reasoning.
• Apply advanced prompt engineering techniques to improve accuracy, determinism, and robustness of LLM systems.
• Establish AgentOps practices, including observability, tracing, logging, and performance monitoring for production-grade AI systems.
• Build multimodal AI solutions, integrating text with images or structured data to support complex enterprise use cases.
• Apply harness engineering practices to systematically design, test, and evaluate AI/agent workflows across different scenarios.
• Develop reusable agent tooling and integrations, including Model Context Protocol and Agent-to-Agent communication patterns.
• Collaborate with cross-functional stakeholders to translate business problems into scalable GenAI-driven solutions.

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 within a cloud infrastructure.
• Deep expertise in RAG architectures, including embedding generation, retrieval optimization, grounding, and context management.
• Proficiency in prompt engineering techniques.
• Hands-on experience building and deploying LLM-powered applications and agent-based systems in production environments.
• Strong Python programming skills with experience in tooling, function-calling, and agent-driven integrations.

Preferred Qualifications

• Experience implementing AgentOps practices, including observability, tracing, logging, and performance evaluation of AI systems.
• Experience designing context engineering strategies.
• Experience building ML/AI pipelines, including automation, orchestration, and CI/CD integration.
• Solid expertise in NLP and text processing.
• Exposure to advanced agentic patterns, multimodal AI systems, and LLMOps/MLOps practices.

Skills PythonRAG ArchitecturesPrompt EngineeringLangChainMachine LearningNLPLLMs

Benefits

• Wellness programs
• Visa / relocation support