Senior AI Engineer

SYSGEN RPO; Philippines; On-site; PHP 1,200,000 - 2,000,000; Full time

Job summary

Sysgen RPO is seeking a Senior Agentic AI Engineer to design multi-agent systems and scalable data-driven workflows. You will implement agentic architectures, orchestrate LLMs, and build interfaces for non-technical teams.

You will collaborate with Data Scientists, write robust Python, and connect agents to Databricks, Power BI, and cloud APIs to deliver repeatable client solutions.

Qualifications

• 3+ years of software engineering experience with Python.
• 1+ year hands-on experience building with LLMs (prompt engineering, RAG, function calling, agent frameworks).
• Experience with at least one agent orchestration framework (LangChain, LangGraph, AutoGen, CrewAI).
• Understanding of API design, microservices, and event-driven architectures.
• Experience with cloud platforms (Azure preferred).
• Familiarity with vector databases, embeddings, and retrieval-augmented generation patterns.
• Strong debugging and problem-solving skills in distributed systems.

Responsibilities

• Design and build multi-agent systems using LLM orchestration frameworks (LangChain, LangGraph, CrewAI, or custom).
• Build agentic wrappers around existing data science models (MMM, forecasting, RBA, incrementality).
• Set up Genie spaces for client data exploration and self-service analytics.
• Develop tool-use patterns that connect agents to Databricks, Power BI, and other platform APIs.
• Write production-grade Python code with proper error handling, logging, and monitoring.
• Collaborate with Data Scientists to understand model inputs/outputs and build reliable agent interfaces.
• Participate in architecture reviews and contribute to the team's agentic design patterns and reusable components.

Skills

Python

LLMs

Agent orchestration

API design

Cloud platforms

Vector databases

Distributed systems

Tools

Databricks

Genie

Job description

Exploring career opportunity? Sysgen RPO is hiring Senior Agentic AI Engineer!

About the job:

• Direct hire with client from IT Services and Consulting industry
• Full-time and permanent role

Role Summary

Build multi-agent systems that turn data intelligence into automated, client-facing workflows. You will design and implement agentic architectures that make measurement models, data pipelines, and media optimization tools accessible through natural interfaces. The goal: solutions that are cheap to build, cheap to run, and easy for non-technical teams to use.

Key Responsibilities

• Design and build multi-agent systems using LLM orchestration frameworks (LangChain, LangGraph, CrewAI, or custom)
• Build agentic wrappers around existing data science models (MMM, forecasting, RBA, incrementality) so they can be queried and used conversationally
• Set up and configure Genie spaces for client data exploration and self-service analytics
• Develop tool-use patterns that connect agents to Databricks, Power BI, and other platform APIs
• Write production-grade Python code with proper error handling, logging, and monitoring
• Collaborate with Data Scientists to understand model inputs/outputs and build reliable agent interfaces
• Participate in architecture reviews and contribute to the team's agentic design patterns and reusable components

Required Qualifications

• 3+ years of software engineering experience with strong Python skills
• 1+ year hands-on experience building with LLMs (prompt engineering, RAG, function calling, agent frameworks)
• Experience with at least one agent orchestration framework (LangChain, LangGraph, AutoGen, CrewAI)
• Understanding of API design, microservices, and event-driven architectures
• Experience with cloud platforms (Azure preferred)
• Familiarity with vector databases, embeddings, and retrieval-augmented generation patterns
• Strong debugging and problem-solving skills in distributed systems

Preferred Qualifications

• Experience with Databricks and/or Genie
• Background in media, advertising, or marketing technology
• Experience building conversational interfaces or chatbot systems
• Familiarity with MLOps practices and model serving infrastructure
• Open-source contributions or personal projects demonstrating agentic AI work