Lead AI Engineer

We are looking for a Lead AI Engineer to design and deliver AI solutions, including chatbots, Q&A systems, and workflow systems for agents. This position requires staying informed about LLM advancements and driving innovation in AI projects. Join us to expand your expertise in AI engineering and create impactful solutions tailored to client needs.

Responsibilities

Design AI applications such as chatbots, Q&A platforms, and agent workflows Collaborate with clients to identify needs, opportunities, and recommend LLM-based solutions Develop data pipelines, prompt strategies, and datasets to support effective AI models Evaluate AI systems to ensure accuracy, security, scalability, and compliance with industry standards Research and validate technical feasibility while demonstrating business value Stay informed about LLM technologies, frameworks, and methodologies to improve solutions Requirements Proficiency in Python and experience with web frameworks like FastAPI Background in leading and mentoring engineering teams Understanding of AI development lifecycles Flexibility to use rapid UI prototyping tools like Streamlit or Gradio Familiarity with LLM platforms and APIs such as OpenAI, Anthropic, Amazon Bedrock, and Gemini, along with frameworks like Lang.

Graph and Llama. Index Knowledge of advanced AI integration patterns like RAG and Agents Skills in deploying AI solutions at scale with a focus on performance and cost-efficiency Experience assessing generative AI quality using retrieval, classification, or LLM-based metrics Proven background in AI engineering and delivering machine learning-based solutions Competency in problem-solving with strong attention to detail Strong written and verbal English communication skills (B2+) Nice to have Background in designing experiments and conducting A/B testing for model optimization Understanding of retrieval systems, vector search, and ranking algorithms Familiarity with protocols like MCP, A2A, and ACP Experience deploying AI solutions to cloud platforms such as Azure OpenAI, Amazon Bedrock, or GCP Vertex AI; flexibility to leverage on-premise options like vLLM Background in enterprise AI platforms such as AWS Agent.

Core, Databricks Agent. Bricks, or Azure AI Foundry Skills in using observability and monitoring frameworks and tools