- Seeking an experienced Senior AI/ML Engineer specialized in Generative AI and Agentic Systems.

- Role focuses on the end-to-end design, development, optimization, and deployment of autonomous and semi-autonomous AI agents.

- Architect multi-agent orchestration systems, design enterprise-grade Retrieval-Augmented Generation (RAG) pipelines, and implement production-ready MLOps infrastructure utilizing Google Cloud Platform (GCP) and containerized environments.

- Minimum of 3 years of professional experience in Machine Learning or AI Engineering with a strong foundation in MLOps practices.

- At least 1 to 2 years of hands-on experience specifically designing and implementing LLM-based, generative AI, or agentic systems in production.

- Expert-level Python programming skills and experience with standard machine learning libraries such as PyTorch, Tensor Flow, or Scikit-learn.

- Strong theoretical and practical understanding of deep learning, Natural Language Processing (NLP), and Transformer architectures.

- Hands-on experience using agentic frameworks such as Lang Chain, Lang Graph, Llama Index, CrewAI, or Vertex AI Agent Builder.





- Proven experience with Google Cloud Platform (GCP) and container services including Docker, Kubernetes/GKE, Cloud Run, and Cloud Functions.

- Proven experience working with vector indexing, semantic search, and databases like Vertex AI Vector Search, AlloyDB, or equivalents.

- Solid understanding of database systems (SQL/NoSQL) and building or consuming REST and GraphQL APIs.

- Experience with Terraform, Git, and automated CI/CD tools like Cloud Build, Git Lab CI, or Jenkins.

- Experience setting up monitoring solutions such as Prometheus, Cloud Logging, or Lang Smith, and evaluating LLM outputs for quality and safety.

- Excellent troubleshooting, debugging, and analytical skills for diagnosing complex agent behavior, tool failures, and infrastructure bottlenecks.

- Exceptional collaborative and communication skills to effectively translate complex technical constraints to cross-functional stakeholders.

- GCP Qualified Machine Learning Engineer or Google Professional Cloud Architect certifications are highly desired.

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📌 AI/ML Architect (India)
🏢 Ford Motor
📍 India