
Job Overview:
We are seeking a highly experienced and innovative Senior AI Engineer with a strong background in Generative AI, including LLM fine-tuning and prompt engineering. This role requires hands-on expertise across NLP, Computer Vision, and AI agent-based systems, with the ability to build, deploy, and optimize scalable AI solutions using modern tools and frameworks.
Required Skills & Qualifications:
- Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related field.
- 5+ years of hands-on experience in AI/ML solution development.
- Proven expertise in fine-tuning LLMs (e.g., LLaMA, Mistral, Falcon, GPT-family) using techniques like LoRA, QLoRA, PEFT.
- Deep experience in prompt engineering, including zero-shot, few-shot, and retrieval-augmented generation (RAG).
- Proficient in key AI libraries and frameworks:
- LLMs & GenAI: Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, Diffusers
- NLP: SpaCy, NLTK.
- Vision: OpenCV, MMDetection, YOLOv5/v8, Detectron2
- MLOps: MLflow, FastAPI, Docker, Git
- Familiarity with vector databases (Pinecone, FAISS, Weaviate) and embedding generation.
- Experience with cloud platforms like AWS, GCP, or Azure, and deployment on in house GPU-backed infrastructure.
- Strong communication skills and ability to convert business problems into technical solutions.
Preferred Qualifications:
- Experience building multimodal systems (text + image, etc.)
- Practical experience with agent frameworks for autonomous or goal-directed AI.
- Familiarity with quantization, distillation, or knowledge transfer for efficient model deployment.
Key Responsibilities:
- Design, fine-tune, and deploy generative AI models (LLMs, diffusion models, etc.) for real-world applications.
- Develop and maintain prompt engineering workflows, including prompt chaining, optimization, and evaluation for consistent output quality.
- Build NLP solutions for Q&A, summarization, information extraction, text classification, and more.
- Develop and integrate Computer Vision models for image processing, object detection, OCR, and multimodal tasks.
- Architect and implement AI agents using frameworks such as LangChain, AutoGen, CrewAI, or custom pipelines.
- Collaborate with cross-functional teams to gather requirements and deliver tailored AI-driven features.
- Optimize models for performance, cost-efficiency, and low latency in production.
- Continuously evaluate new AI research, tools, and frameworks and apply them where relevant.
- Mentor junior AI engineers and contribute to internal AI best practices and documentation.

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