Manager AI Engineering

Lead architecture and development of enterprise-scale multi-agent AI systems and multimodal generative AI pipelines utilizing cutting-edge LLM frameworks and transformer-based models.

Drive production deployment of retrieval-augmented generation (RAG) systems integrating vector databases and knowledge graphs for semantic retrieval and reasoning.

Establish and oversee LLMOps and MLOps pipelines for reliable, scalable AI delivery including model fine-tuning, prompt engineering, and responsible AI governance implementations.

Bachelor's or Master's degree in Computer Science, AI/ML, or Engineering.

Significant hands-on experience leading and delivering complex generative AI or ML engineering programs in production environments.

Expertise in LLM application design, agentic systems, RAG pipelines, and practical use of frameworks such as LangGraph, LangChain, and open-source foundation models.

Strong Python engineering skills including asynchronous programming and API development; proficiency with SQL; experience with cloud AI infrastructure (AWS, Azure, or GCP) and MLOps tools (MLflow, etc.)

Experienced technical leader with demonstrated ability to design and ship next-generation AI systems combining multiple AI modalities and agents to solve enterprise-scale challenges.

Deep domain expertise with LLM ecosystems (OpenAI, Anthropic, Gemini, Hugging Face, etc.) and advanced generative AI engineering patterns.

Proficient communicator and stakeholder manager who translates complex Gen AI concepts to business value and leads cross-functional delivery teams effectively.