Senior AI Engineer

Senior AI Engineer / Player-Coach

Purpose: Own our Generative AI technical vision. You will rapidly prototype and lead a dedicated team of two engineers to launch our companys first intelligent search and content automation systems.

Role Summary

Were looking for a hands-on Gen AI pioneer who can architect code and mentor. This is a player-coach role where youll be building foundational systems while guiding your team. You will partner daily with product and engineering leadership to transform business goals into cutting-edge shippable LLM-powered solutions.

Key Responsibilities

• Architect & Build RAG Systems: Design develop and deploy sophisticated Retrieval-Augmented Generation (RAG) systems to power our next-generation search and discovery experience.
• Develop & Fine-Tune LLMs: Lead the development of advanced generative models for nuanced tasks like automated content creation summarization and metadata enrichment.
• Own the Gen AI Stack: Select provision and optimize our stack leveraging managed services like Azure OpenAI or AWS Bedrock or self-hosting models on GPU infrastructure. You will establish best practices for repo structure CI/CD and model/prompt versioning.
• Implement LLMOps: Embed robust observability using tools like OpenTelemetry and Prometheus. This includes tracking standard metrics (latency cost accuracy) and specialized monitoring for hallucination toxicity and data drift.
• Lead & Mentor: Hire coach and develop ML talent. Set the standard for high-quality code rigorous experimentation and rapid iteration within the Gen AI domain.

Must-Have Skills

• Production LLM Experience: 5 years in Python with demonstrable success in productionizing LLM applications using modern frameworks like DSPY LangChain LlamaIndex or Hugging Face Transformers.
• RAG Expertise: Deep practical knowledge of RAG architecture including advanced prompt engineering chunking strategies and proficiency with vector databases (e.g. Pinecone Weaviate Milvus).
• Cloud Proficiency: Expertise with managed LLM services (Azure OpenAI Service or AWS Bedrock). Strong foundational cloud skills in either Azure or AWS for compute orchestration (AKS/EKS) serverless functions and storage.
• MLOps Acumen: Solid experience with Docker CI/CD pipelines (e.g. GitHub Actions Argo) and model registries.
• Leadership & Communication: Proven ability to lead small highly technical teams and clearly communicate complex concepts to stakeholders.

Nice-to-Have Skills

• Experience with agentic workflows (e.g. AutoGen CrewAI).
• Familiarity with multi-modal models (text image etc.).
• Knowledge of advanced LLM fine-tuning techniques (e.g. LoRA QLoRA).
• Strong SQL skills (especially with ClickHouse) and a keen eye for inference cost optimization.

Employment Type : Full Time
Experience: years
Vacancy: 1