SENIOR APPLIED AI ENGINEER | AI Platform

Our client building next-generation AI platform - generative AI simulation-powered search engine that allows non-technical users to query complex datasets and automate workflows.

The Role: Senior hands-on role - own end-to-end agentic systems stack from LLM orchestration and tool-use to evaluation and production deployment. Work directly with founding and senior leadership to set technical direction and ship with product and research teams.

Key Responsibilities

Agent Development & Architecture

• Architect and build autonomous AI agents capable of querying data answering data-based questions and automating complex enterprise workflows for non-SQL / non-technical users
• Design multi-step reasoning tool-use function calling and RAG pipelines - enabling agents to interact with data lakes feature stores APIs
• Implement agentic frameworks (LangGraph AutoGen CrewAI or custom orchestration) with robust state management memory and planning
• Build evaluation harnesses for agent reliability accuracy safety

LLM & Generative AI Platform

• Fine-tune and deploy LLMs for enterprise-specific tasks - instruction tuning RLHF/DPO domain adaptation
• Optimize inference for low-latency cost-efficient production - quantization caching batching GPU/TPU scheduling
• Build retrieval systems (vector DBs - Pinecone Weaviate Milvus Qdrant) for enterprise knowledge bases
• Partner with Data Engineering to ensure feature store and data lake are agent-ready

Data & Tool Integration

• Create tools and connectors for agents to interact with enterprise systems - data warehouses lakehouses (Databricks Snowflake) APIs
• Implement observability logging tracing for agentic workflows (LangSmith Langfuse OpenTelemetry)

Candidate Profile - Senior Level 7-12 Years

• Proven Agent Builder: 3 years building production LLM agents / RAG systems / AI copilots that query data and automate workflows. Portfolio of shipped agents
• LLM Stack: Deep hands-on with LLMs (GPT-4 Claude Llama Mistral) prompt engineering function calling tool-use RAG vector DBs LangChain/LlamaIndex/LangGraph
• Production AI: Reliability latency evaluation safety. MLOps / LLMOps
• Core Engineering: Strong Python SQL Spark. Databricks/Snowflake
• Enterprise AI Mindset: Simplifying complex data queries into natural language - as technical as possible as commercial as possible