AI Engineer with Data Science at Turing

AI Engineer (Data Science) | Remote – India | EST Overlap Required | Immediate Start

Turing is seeking a Mid-Senior AI Engineer with a strong Data Science background to design, build, and scale AI-powered applications. This is a single-position engagement requiring immediate to 1-week availability, with a 4-hour EST overlap. Candidates must have 5–8 years of software engineering experience and proven hands-on expertise in Generative AI, LLMs, and modern AI frameworks.

Key Responsibilities

• Design, develop, and deploy scalable AI-powered applications and intelligent services.
• Architect and implement solutions using LLMs, Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, and vector search technologies.
• Apply strong Data Structures and Algorithms principles to build efficient, high-performance systems.
• Develop and optimize backend services, APIs, and AI pipelines using Python.
• Integrate AI models with internal applications, cloud services, and third-party platforms.
• Optimize AI applications for performance, latency, scalability, reliability, and cost-efficiency.
• Evaluate emerging AI models and frameworks to drive innovation and continuous improvement.
• Conduct code reviews and establish engineering best practices for AI development.
• Mentor junior engineers and provide technical guidance on solution design.
• Collaborate cross-functionally with Product Managers, Data Scientists, QA, and Engineering teams.
• Troubleshoot production issues and drive continuous system improvements.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
• 5–8 years of professional Data Science experience (strong background is a must).
• At least 3 years of hands-on experience developing AI or Machine Learning applications.
• Strong expertise in Python and object-oriented programming.
• Solid understanding of Data Structures, Algorithms, design patterns, and software architecture.
• Hands-on experience with LLMs such as OpenAI, Anthropic, Google Gemini, or open-source models.
• Experience with AI frameworks like LangChain, LlamaIndex, or Semantic Kernel.
• Proven experience implementing RAG, vector embeddings, and semantic search solutions.
• Familiarity with vector databases: Pinecone, Chroma, Weaviate, FAISS, or Milvus.
• Experience developing RESTful APIs and microservices.
• Strong knowledge of SQL and NoSQL databases.
• Proficiency with Git, CI/CD pipelines, automated testing, and engineering best practices.