Description

Responsibilities include:

Design, develop, and deploy scalable machine learning models, AI solutions, and graph-based applications to address complex business challenges.

Build, maintain, and optimize cloud-native data pipelines, Knowledge Graph architecture, and MCP serving platforms on GCP.

Develop and support LLM-powered agent systems, including RAG, tool integrations, embeddings, and model-serving capabilities.

Automate ML model training, deployment, monitoring, and lifecycle management using MLOps, CI/CD, and Infrastructure as Code practices.

Monitor system performance, data quality, reliability, and observability through dashboards, alerting, tracing, and incident response processes.

Collaborate with cross-functional teams to onboard enterprise data sources, establish data governance standards, and ensure the accuracy and scalability of AI-driven solutions.

Required Qualifications:

Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, Software Engineering, or a related technical field.

7+ years of IT experience, including 3+ years of software development and 2+ years of AI/ML engineering experience.

Strong hands-on experience with Python, Java, GCP services (Vertex AI, BigQuery, Dataflow, GKE), and production-grade AI/ML solution deployment.

Experience building Knowledge Graphs, LLM/Agent-based systems, MLOps pipelines, and scalable cloud-native data platforms with observability and security best practices

Key Skills

Education

Any Graduate