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We are looking for a Senior AI Engineer to design, build and scale our next-generation AI and Large Language Model (LLM) applications. In this role, you will lead the technical development of advanced AI workflows, work directly with clients to turn their ideas into reality and help mentor our growing team.
Responsibilities
- Architect and implement scalable AI applications, including chatbots, search platforms and autonomous agent workflows
- Collaborate directly with business stakeholders to understand their challenges and recommend smart, LLM-driven solutions
- Creation of data pipelines, design of smart prompt strategies and development of testing frameworks to ensure AI models are safe, accurate and cost-effective
- Establish coding standards, perform code reviews and mentor junior developers in AI best practices
- Run quick experiments and build prototypes to test new models
- Stay ahead of the curve with emerging AI research and tools
Requirements
- 3+ years of proven background as a Senior Software Engineer delivering production-grade AI, Machine Learning or LLM-based solutions
- Proficiency in Python (especially web frameworks like FastAPI) and understanding of NLP concepts (semantic similarity, tokenization, text classification)
- Hands-on expertise in modern AI patterns, particularly RAG (Retrieval-Augmented Generation) and AI Agents
- Familiarity with major LLM APIs (OpenAI, Anthropic, Bedrock) and framework tools (LangGraph, LlamaIndex)
- Background in deploying AI applications at scale, managing cloud costs and evaluating model quality (retrieval metrics, LLM-based evaluation)
- Capability to quickly spin up user interfaces using Streamlit, Gradio or similar tools
- Skills in explaining complex technical ideas clearly to both developer teams and non-technical clients
- English proficiency at B2 level or higher
Nice to have
- Development experience with TypeScript
- Experience incorporating AI into the SDLC (GitHub Copilot, Cursor)
- Expertise in AWS or Azure (specifically Azure OpenAI or AWS Bedrock)
- Familiarity with Databricks (MLflow, AgentBricks) for data or model workflows
- Knowledge of advanced search/retrieval systems (vector databases, semantic search, rerankers)
- Understanding of emerging open-source protocols (Model Context Protocol - MCP) or LLM monitoring tools (LangSmith, Arize Phoenix)