SENIOR APPLIED AI ENGINEER |- AI Platform

Newbridge; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Newbridge is building a next-generation AI platform that combines generative AI and simulation-powered search to help non-technical users query complex datasets and automate workflows. The Senior hands-on role owns the end-to-end agentic systems stack, from LLM orchestration to production deployment, working with founders and leadership.

You will architect autonomous AI agents, design multi-step pipelines, and implement robust tooling with data lakes, feature stores, APIs, and observability.

Qualifications

• 3+ years building production LLM agents / RAG systems / AI copilots that query data and automate workflows.
• Deep hands-on with LLMs (GPT-4, Claude, Llama, Mistral) and prompt engineering, function calling, tool-use, RAG, vector DBs, LangChain/LlamaIndex/LangGraph.
• Reliability, latency, evaluation, safety in Production AI / MLOps / LLMOps.
• Strong Python, SQL, Spark skills; Databricks/Snowflake experience.
• Enterprise AI mindset: simplify complex data queries into natural language, both technical and commercial.

Responsibilities

• 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 with robust state management, memory, and planning; build evaluation harnesses for agent reliability, accuracy and safety.

Skills

Agent builder

LLM stack

Production AI

Core engineering

Enterprise AI mindset

Tools

LangGraph

AutoGen

CrewAI

LangChain

LlamaIndex

Pinecone

Weaviate

Milvus

Qdrant

Databricks

Snowflake

Job description

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