Senior AI Engineer

We are seeking a senior Data AI Engineer to design and develop AI applications that leverage large language models and advanced integration techniques.
You will work closely with clients to build solutions such as chatbots and Q&A platforms that deliver measurable business value. In this role, you will have the opportunity to lead AI application development, manage data pipelines, and stay at the forefront of evolving LLM technologies. If you have a passion for AI engineering and enjoy collaborating with clients to solve complex problems, we encourage you to apply.
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 designing experiments, conducting A/B tests, and iterating on models based on user feedback
Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
Familiarity with emerging protocols such as MCP, A2A, ACP, etc.
Experience deploying to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (e.g., vLLM)
Experience with enterprise AI platforms such as AWS AgentCore or Databricks AgentBricks or Google Agents Space, or Azure AI Foundry
Experience with observability and monitoring tools and frameworks