Senior AI Engineer

We are looking for a Senior AI Engineer who excels at developing custom AI solutions for clients across diverse industries.
Your work will involve designing, implementing, and optimizing chat-based systems, Q&A tools, and agent-driven applications using the latest advances in generative AI. You will partner closely with client teams, guiding them through best practices and helping them leverage state-of-the-art technologies to achieve their goals.
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
Evaluate and refine AI system performance, ensuring outputs are accurate, secure, scalable, and compliant with industry regulations
Conduct research and rapid prototyping to validate technical feasibility and demonstrate business value
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
Deep understanding of the AI development lifecycle
NLP expertise (classification, NER, retrieval, summarization, etc)
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
Experience with MLflow or alternative MLOps frameworks
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, Databricks Agent Bricks, Google Agents Space, or Azure AI Foundry
Experience with observability and monitoring tools and frameworks
Knowledge of model training and fine-tuning techniques
Proven ability to build and maintain reliable data pipelines and workflows using Airflow, Argo Workflows, or similar tools