Urwah Admin

DM Clinical Research

<div>We are seeking an AI Applications Engineer with deep expertise in AI systems development to join our engineering team. In this role, you&rsquo;ll bridge the gap between ML research and real-world software delivery &mdash; designing, developing, and deploying intelligent applications powered by modern AI technologies including LLMs, multimodal models, and agentic workflows. You'll work closely with data scientists, ML engineers, and product managers to ship cutting-edge, scalable AI-powered features across web, backend, and mobile platforms. 
DUTIES &amp; RESPONSIBILITIES<ul><li>
Design and build AI-native applications leveraging LLMs (e.g., OpenAI, Anthropic, Mistral) and multimodal models.</li><li>
Architect and implement agent-based workflows using frameworks like LangGraph, CrewAI, and AutoGen.</li><li>
Develop production-grade Python services using FastAPI or similar frameworks to expose AI functionalities via APIs.</li><li>
Fine-tune and serve custom LLMs for text, voice, and multimodal inputs; implement Retrieval-Augmented Generation (RAG) pipelines.</li><li>
Integrate vector search systems (e.g., Weaviate, Qdrant, Pinecone) for semantic memory and contextual reasoning.</li><li>
Use modern orchestration tools like LangChain, Flowise, Haystack, or n8n to prototype and scale intelligent flows.</li><li>
Leverage the OpenAI Function Calling / Tools API and Model Context Protocol (MCP) to build structured, dynamic LLM interactions.</li><li>
Implement continuous evaluation loops using synthetic data, human feedback (RLHF), and evaluation frameworks like Ragas or DeepEval.</li><li>
Collaborate with ML/infra teams to containerize, deploy, and monitor models using tools like Docker, MLflow, BentoML, or Kubernetes.</li><li>
Build scalable, secure, and efficient AI feature delivery pipelines across web and mobile platforms.</li><li>
Stay current with developments in foundation models, agent frameworks, multimodal AI, and open-source toolkits.</li></ul>
KNOWLEDGE &amp; EXPERIENCE
Education:<ul><li>
Bachelor's or Master&rsquo;s degree in Computer Science, Software Engineering, Artificial Intelligence, or related discipline.</li></ul>
Experience:<ul><li>
2&ndash;4 years of experience building and deploying AI/ML-powered software.</li><li>
Proven track record of delivering LLM-integrated applications and/or agentic workflows in production.</li><li>
Experience in any of the following domains is a plus: NLP, computer vision, multimodal models, or conversational AI.</li></ul>
Knowledge and Skills:<ul><li>
Proficient in Python and building production-grade RESTful APIs (FastAPI preferred).</li><li>
Experience working with foundation model APIs (OpenAI, Claude, Gemini, Mistral, Cohere).</li><li>
Familiarity with LangChain, LangGraph, CrewAI, Flowise, or similar frameworks.</li><li>
Experience implementing RAG pipelines and retrieval layers with vector databases (Pinecone, Qdrant, Weaviate, FAISS).</li><li>
Understanding of prompt engineering, structured memory (MCP), tool calling, and multi-turn conversation flows.</li><li>
Comfortable with tools like MLflow, Weights &amp; Biases, or BentoML for model versioning and tracking.</li><li>
Ability to integrate with third-party services, RESTful APIs, and webhooks (Zapier, n8n, etc.).</li><li>
Familiarity with MLOps and CI/CD workflows for AI applications.</li><li>
Experience working with containerized environments (Docker, Kubernetes).</li><li>
Git, agile software development practices, and collaborative code workflows.</li><li>
Experience with speech recognition (Whisper), text-to-speech (ElevenLabs), or multimodal APIs (e.g., GPT-4o).</li></ul></div>

AI Applications Engineer

Join DM Clinical Research and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

DM Clinical Research

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AI Applications Engineer