Senior Data Scientist/AI engineer

CHI Software is a global software development services provider delivering AI-driven solutions, cloud services and data engineering across EdTech, FinTech, HealthTech. We help businesses modernize, scale, and unlock new value through the latest technologies.
We are looking for Senior Data Scientist/AI engineer.

Job Summary

Our client is a leader in Advertising Resource Management software, driving marketing transformation in the age of agentic AI. At the core of the platform is an open enterprise ecosystem that leverages autonomous AI agents to augment human teams across the marketing and advertising value chain, connecting marketing performance with measurable business impact.

We are looking for a Senior Data Scientist to design and build advanced data-driven and machine learning capabilities within a modern SaaS platform.

In this role, you will work closely with Product, Engineering, and domain experts to transform complex business challenges into scalable AI-driven solutions. The position covers the full data science lifecycle, from problem definition and research to production-ready systems.

A strong focus of this role is on building agent-based AI systems, leveraging LLMs and modern orchestration frameworks to automate complex workflows and decision-making processes.

Key Responsibilities

1. Agent-Based AI Solutions (Core Focus)

Design and develop autonomous and semi-autonomous AI agents to automate multi-step business workflows
Build and integrate LLM-powered systems using modern orchestration frameworks and tool-usage patterns
Develop agents capable of interacting with internal systems and external APIs to execute actions and retrieve real-time data
Implement Human-in-the-Loop (HITL) mechanisms, ensuring safe, controlled, and auditable AI decision-making
Design evaluation frameworks, guardrails, and monitoring systems for reliable agent behavior in production

2. Predictive Modeling & Decision Intelligence

Develop predictive models to support planning, forecasting, and optimization use cases
Build simulation frameworks to evaluate “what-if” scenarios and support data-driven decision-making
Apply statistical and machine learning techniques to optimize performance across key business metrics

3. Real-Time Optimization & Automation

Design and implement real-time decisioning systems and optimization algorithms
Build scalable pipelines for continuous data processing and model inference
Improve system performance through experimentation, A/B testing, and iterative enhancements
Collaborate with cross-functional teams and contribute to production-ready AI solutions