Lead AI Engineer

Job Description

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level About the Role We’re seeking an experienced and forward-thinking Lead AI Engineer to head the development of cutting-edge AI applications leveraging large language models (LLMs) and generative AI techniques. In this high-impact role, you will guide the architecture, deployment, and optimization of AI systems that power real-world, intelligent applications. You’ll be at the intersection of research and engineering, leading a team of top-tier AI engineers while shaping the future of AI capabilities within the organization. What You’ll Do Architect AI Solutions Design and lead the development of end-to-end AI systems that leverage LLMs, retrieval-augmented generation (RAG), and autonomous agent frameworks. Model Integration and Optimization Work hands-on with both open-source (Llama, Mistral, Falcon, etc.) and proprietary models (GPT-4, Claude, Gemini), fine-tuning them for specialized applications using proprietary data. Agentic Systems & RAG Build intelligent agents capable of reasoning, planning, and performing multi-step tasks using agentic architectures and RAG pipelines with vector databases like FAISS or Weaviate. Production-Grade Engineering Oversee scalable deployment, versioning, and monitoring of AI models in production using modern MLOps practices and cloud-native platforms (AWS, GCP, Azure). Cross-functional Collaboration Partner with data scientists, product managers, and software engineers to transform complex problems into elegant AI-driven products. AI Team Leadership Mentor a team of engineers, drive technical direction, and manage project priorities, sprint planning, and roadmap execution. Innovation & Research Stay ahead of the curve by tracking advancements in the AI/LLM space. Promote a culture of experimentation, rapid prototyping, and responsible AI. Ethics & Evaluation Implement best practices for model interpretability, bias mitigation, and responsible deployment of AI systems. Must-Have Qualifications Experience 5+ years of hands-on experience in AI/ML engineering with a primary focus on NLP and LLMs. Proven experience in designing and deploying production-grade AI systems. Technical Skills Strong command of Python and frameworks like PyTorch , TensorFlow , LangChain , and LlamaIndex . Solid knowledge of transformer architectures , embeddings, fine-tuning techniques, and tokenization. Experience integrating with vector databases (FAISS, Pinecone, Weaviate). Proficiency in designing APIs and working with distributed systems . Familiarity with MLOps , containerization (Docker), and orchestration tools (Kubernetes). Leadership Experience managing engineering teams and projects, with a track record of shipping successful AI solutions. Cloud & Deployment Deep experience with deploying AI systems on AWS , GCP , or Azure , and optimizing workloads for cost and performance. Nice-to-Have Experience working with multi-modal AI models (text, image, video, audio). Knowledge of RLHF (Reinforcement Learning from Human Feedback) methodologies. Contributions to open-source AI projects or peer-reviewed research. Prior experience at a startup or AI research lab .