Curious about the role? What your typical day would look like?

We are looking for a GenAI Machine Learning Engineer (GenAI MLE) with solid hands-on experience in building, deploying, evaluating, and scaling Generative AI and Agentic AI solutions on Google Cloud Platform (GCP).

The ideal candidate will have strong expertise in Google ADK, Vertex AI, Gemini, Agent Engine, RAG, Prompt Engineering, GenAI Evaluation, Python, and MLflow, along with experience in deploying production-grade AI applications using services such as Cloud Run, Google Cloud Storage, BigQuery, and Document AI.

You will work closely with business stakeholders, data scientists, AI architects, and engineering teams to convert GenAI use cases into secure, scalable, reliable, and production-ready AI solutions.

Key Responsibilities

- Design, develop, and deploy Generative AI and Agentic AI applications on GCP.
- Build AI agents and agentic workflows using Google ADK and Agent Engine.
- Work with Vertex AI and Gemini for LLM-based application development.
- Develop RAG-based solutions, including retrieval, grounding, context management, and prompt engineering.
- Implement GenAI evaluation frameworks to assess response quality, accuracy, relevance, groundedness, and overall application performance.
- Build scalable AI applications using Python and integrate enterprise data and APIs.
- Work with GCP services including GCS, BigQuery, Cloud Run,



and Document AI.
- Use MLflow for experiment tracking, model management, and ML/GenAI lifecycle management.
- Support production deployment, monitoring, troubleshooting, and optimization of GenAI solutions.
- Collaborate with Data Scientists, Architects, Engineers, Product teams, and business stakeholders to translate requirements into scalable AI solutions.
- Participate in Agile development practices, sprint planning, reviews, and retrospectives.

Must-Have Skills

- Solid experience in Generative AI / Machine Learning Engineering.
- Hands-on experience with GCP and Vertex AI.
- Strong knowledge of Google ADK, Gemini, and Agent Engine.
- Experience building RAG applications and AI agents.
- Solid understanding of Prompt Engineering and GenAI Evaluation.
- Proficiency in Python.
- Experience with MLflow.
- Hands-on experience with GCS, BigQuery, Cloud Run, and Document AI.
- Good understanding of production deployment and cloud-based AI solutions.
- Strong communication, stakeholder management, and collaboration skills.
- Experience working in an Agile workplace.

Good to Have

- Experience with AWS AI/ML services, particularly:
- AWS SageMaker
- Amazon Bedrock

- Experience with multi-cloud AI/ML environments.
- Exposure to GenAI monitoring, observability, governance, and production optimization.

📌 AIML Engineer-GenAI+GCP (Delhi)
🏢 Tiger Analytics
📍 Delhi