Senior AI Engineer
We are seeking a Senior AI Engineer passionate about modern AI technologies and comfortable navigating the rapidly evolving generative AI landscape.
This position is ideal for candidates experienced in data science and possessing the skills to build AI-powered systems with strong business impacts. Join our innovative team to design, implement, and optimize state-of-the-art generative AI solutions that solve complex real-world problems. Thrive in a forward-thinking work environment with opportunities to learn and grow.
Responsibilities
- Design, implement, and maintain end-to-end AI applications, including chatbots, Q&A platforms, and agent workflows
- Collaborate directly with clients to understand their needs, identify opportunities, and recommend LLM-driven solutions
- Develop and manage robust data pipelines, prompt strategies, and datasets to ensure effective and accurate AI models (Will be +)
- Evaluate and refine AI system performance, ensuring outputs are accurate, secure, scalable, and compliant with industry regulations (Will be +)
- Conduct research and rapid prototyping to validate technical feasibility and demonstrate business value of AI solutions
- Stay current with evolving LLM technologies, frameworks, and methodologies to continuously improve solutions and client outcomes
Requirements
- Strong proficiency in Python, experience with web frameworks like FastAPI or similar
- Understanding of the AI application development lifecycle
- Experience with rapid UI prototyping using Streamlit, Gradio, or similar frameworks
- Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (LangGraph, LlamaIndex, Strands Agents, etc.)
- Knowledge of advanced AI integration patterns (e.g., RAG, Agents)
- Experience deploying AI solutions at scale, with considerations for performance, cost-efficiency, and maintainability
- Proven ability to evaluate generative AI quality using metrics such as retrieval and classification scores, as well as LLM-based evaluation methods
- Proven experience in AI engineering and delivering ML-based solutions
- Strong problem-solving skills and attention to detail
- Excellent communication, collaboration, and interpersonal skills
Nice to have
- Experience with at least one major cloud provider (AWS, GCP, Azure)
- Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical audiences
- Fluency in English (minimum B2 level)
Technologies
- Python, PyTorch, Hugging Face, LangChain
- Vector databases including Qdrant, FAISS, Chroma
- APIs for LLMs such as Azure OpenAI and AWS Bedrock
