AI Engineer
We are seeking a highly experienced and visionary Lead Generative AI Engineer to drive our next generation of AI-powered products. With 8 to 10 years of comprehensive experience inMachine Learning, Deep Learning, and Software Engineering, you will serve as the principal architect for our Generative AI initiatives. You will lead the design, development, and deployment of cutting-edge LLM applications, autonomous agents, and RAG (Retrieval-Augmented Generation) systems that solve complex, enterprise-scale problems. This is a senior leadership role that requires not only deep technical expertise in modern AI frameworks but also the ability to mentor a team of talented engineers and collaborate directly with product stakeholders to define our AI strategy.
Key Responsibilities
• Architectural Leadership: Design, architect, and scale robust Generative AI solutions, in cluding complex RAG pipelines, multi-agent systems, and customized foundation models.
• Model Engineering & Fine-Tuning: Evaluate state-of-the-art open-source and proprietary LLMs (e.g., GPT-4, Gemini, Llama 3, Claude). Lead the fine-tuning (PEFT, LoRA, QLoRA) and alignment (RLHF, DPO) of models for domain-specific enterprise use cases.
• System Optimization: Optimize LLM inference for latency, throughput, and cost using ad vanced techniques such as quantization, vLLM, TensorRT-LLM, and prompt caching.
• LLMOps & Infrastructure: Establish enterprise-grade LLMOps pipelines for continuous in tegration, deployment, monitoring, and evaluation (e.g., managing model drift, hallucination tracking, and guardrails).
• Technical Mentorship: Mentor and guide mid-level and junior AI engineers, fostering a cul ture of technical excellence, continuous learning, and rigorous code quality.
• Cross-Functional Collaboration: Partner seamlessly with Product Managers, Data Scientists, and Cloud Architects to translate business requirements into scalable, secure, and responsible AI products.
Required Qualifications
• Experience: 8–10 years of hands-on industry experience in Software Engineering, Machine Learning, or Applied AI, with at least 2+ years completely dedicated to Generative AI, LLMs, and NLP.
• Programming: Expert-level proficiency in Python and writing production-ready, highly opti mized, and maintainable code.
• AI/ML Frameworks: Deep expertise in deep learning frameworks (PyTorch, TensorFlow) and the modern GenAI stack (Hugging Face Transformers, LangChain, LlamaIndex).
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• Vector Infrastructure: Extensive experience implementing and scaling Vector Databases (e.g., Pinecone, Milvus, Weaviate, or Qdrant) for high-performance retrieval systems.
• Cloud & Deployment: Proven track record of deploying ML models in production environ ments using AWS, GCP, or Azure, leveraging containerization (Docker, Kubernetes) and server less architectures.
• Education: Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Mathe matics, or a highly related technical field.
Preferred Qualifications (Nice to Have)
• Experience building autonomous AI agents and tool-use (function calling) workflows.
• Strong understanding of Data Security, Privacy, and Responsible AI principles (e.g., handling PII in LLM pipelines, implementing AI guardrails like NeMo Guardrails).
• Open-source contributions to major AI/ML libraries or published research papers in top-tier AI conferences (NeurIPS, ACL, EMNLP).
• Experience with multi-modal Generative AI (image, audio, and video generation models).
To apply, please submit your resume, portfolio/GitHub, and a brief description of the most complex AI system you have architected into production.
Posted March 5, 2026