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 unique needs, identify opportunities, and recommend LLM-driven approaches
- Develop and manage robust data pipelines, prompt strategies, and datasets that ensure effective and accurate AI models
- Evaluate and refine the performance of AI systems, 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 methods to continuously improve solutions and client outcomes
Requirements
- Strong proficiency in Python
- Deep understanding of the AI/LLM development lifecycle, including CI/CD, version control, testing, MLOps and LLMOps
- NLP expertise (classification, NER, retrieval, summarization) and experience with generative AI evaluation techniques
- Proven ability to build and maintain reliable data pipelines and workflows
- Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, LLAMA) and related frameworks (e.g., LangChain, LLamaIndex)
- Knowledge of advanced AI Integration patterns (e.g., RAG, AgenticRAG, agent flows, tool integration)
- Experience deploying AI solutions at scale with considerations for performance, cost-efficiency, and maintainability
- Proven ability to evaluate generative AI quality, using metrics like retrieval and classification scores and LLM-based evaluation methods
- Proven experience in AI engineering and delivering ML-based solutions
- Strong problem-solving abilities 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
- Experience deploying to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (vLLM)
- Experience with monitoring tools and frameworks for evaluating long-term model performance and data drift
- Knowledge how to train and fine-tune models
- Experience with extracting and processing text from diverse sources, including PDFs, websites, and other document formats
