Senior Technical Lead

Preferred/Optional: RAG, Vector DB/Search, MCP, Multi-Agent Systems, Splunk/Observability, Docker/Kubernetes, CI/CD, AIOpsSkill Requirements Primary/Mandatory: Gemini AI, Generative AI/LLMs, Python, GCP, Vertex AI, REST APIs, SQL/BigQuery, Agentic AIJob Summary Agentic AI / Data AI Engineer – GeminiLooking for a Generative AI / Agentic AI Engineer with 6-8 years of overall experience, including strong hands-on experience in Google Gemini and Generative AI/LLM solutions. Strong programming skills in Python, with experience developing AI applications, services, and REST API integrations. Hands-on knowledge of Google Cloud Platform (GCP), Vertex AI, Gemini APIs/SDKs, and BigQuery/SQL.Experience building AI Agents / Agentic AI workflows, including function/tool calling, multi-step reasoning, and API-based actions. Good understanding of RAG, embeddings, vector search, prompt engineering, and LLM grounding techniques. Experience applying AI for data analysis, anomaly detection, incident/root-cause analysis, recommendations, or automated remediation is preferred. Knowledge of Git, CI/CD, Docker/Kubernetes, monitoring/observability, and enterprise data integration is desirable. Strong analytical and problem-solving skills with experience taking GenAI solutions from prototype to production. Primary/Mandatory: Gemini AI, Generative AI/LLMs, Python, GCP, Vertex AI, REST APIs, SQL/BigQuery, Agentic AI

Preferred/Optional: RAG, Vector DB/Search, MCP, Multi-Agent Systems, Splunk/Observability, Docker/Kubernetes, CI/CD, AIOpsKey Responsibilities Agentic AI / Data AI Engineer – GeminiLooking for a Generative AI / Agentic AI Engineer with 6-8 years of overall experience, including strong hands-on experience in Google Gemini and Generative AI/LLM solutions. Strong programming skills in Python, with experience developing AI applications, services, and REST API integrations. Hands-on knowledge of Google Cloud Platform (GCP), Vertex AI, Gemini APIs/SDKs, and BigQuery/SQL.Experience building AI Agents / Agentic AI workflows, including function/tool calling, multi-step reasoning, and API-based actions. Good understanding of RAG, embeddings, vector search, prompt engineering, and LLM grounding techniques. Experience applying AI for data analysis, anomaly detection, incident/root-cause analysis, recommendations, or automated remediation is preferred. Knowledge of Git, CI/CD, Docker/Kubernetes, monitoring/observability, and enterprise data integration is desirable. Strong analytical and problem-solving skills with experience taking GenAI solutions from prototype to production. Primary/Mandatory: Gemini AI, Generative AI/LLMs, Python, GCP, Vertex AI, REST APIs, SQL/BigQuery, Agentic AI

Preferred/Optional: RAG, Vector DB/Search, MCP, Multi-Agent Systems, Splunk/Observability, Docker/Kubernetes, CI/CD, AIOpsSkill Requirements Primary/Mandatory: Gemini AI, Generative AI/LLMs, Python, GCP, Vertex AI, REST APIs, SQL/BigQuery, Agentic AI

Preferred/Optional: RAG, Vector DB/Search, MCP, Multi-Agent Systems, Splunk/Observability, Docker/Kubernetes, CI/CD, AIOpsOther Requirements