Job Summary
We are looking for an experienced AI Developer to design, develop, test, and deploy enterprise-grade Generative AI and Agentic AI solutions leveraging the Google AI ecosystem, including Gemini models, Vertex AI, Google AI Studio, Agent Development frameworks, RAG architectures, and AI evaluation/testing methodologies. The candidate will be responsible for building intelligent AI agents, orchestrating multi-agent workflows, integrating enterprise systems, and ensuring production-grade reliability, security, and governance of AI solutions.
Key Responsibilities
AI Solution Development
Design and develop Generative AI applications using Gemini models.
Build enterprise AI assistants, copilots, chatbots, and AI agents.
Develop Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories.
Integrate AI capabilities with enterprise applications, APIs, databases, and cloud services.
Agentic AI EngineeringDesign and implement autonomous and multi-agent systems.
Build agent orchestration workflows using planning, reasoning, memory, and tool-calling capabilities.
Develop agents that can interact with APIs, enterprise tools, databases, SharePoint, and business applications.
Implement Human-in-the-Loop (HITL) mechanisms for critical decision workflows.
Develop agent guardrails and safety controls.
Google AI Platform Expertise
Build and deploy AI solutions using:Google Gemini Models
Vertex AI
Google AI Studio
Vertex AI Agent Builder
Vertex AI Search
Vertex AI Extensions
Vertex AI Pipelines
Model Garden
Prompt Management FrameworksAI Testing & EvaluationDesign AI testing frameworks and evaluation pipelines.
Validate:Correctness
Accuracy
Hallucination Rate
Relevance
Groundedness
Safety
Toxicity
Latency
Cost EfficiencyBuild automated regression testing for AI agents.
Perform red-teaming and adversarial testing.
Create benchmark datasets and evaluation metrics.
Production Deployment & Operations
Deploy and monitor AI workloads on Google Cloud Platform (GCP).
Establish observability, monitoring, and AI governance controls.
Optimize model performance, token consumption, latency, and operational costs.
Implement CI/CD and MLOps/LLMOps practices.
Stakeholder CollaborationGather business requirements and convert them into AI solutions.
Collaborate with product owners, architects, data engineers, and business stakeholders.
Provide technical leadership on AI strategy and implementation.Required Technical Skills
Generative AI
Google AI Stack
Agent AI Engineering
RAG & Knowledge Systems
AI Evaluation & Testing
Programming & Engineering
Cloud & DevOpsEducation & Experience
Education
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.Experience2–4+ years in software development.
2–4+ years in AI/ML or Generative AI solutions.
Hands-on experience with Gemini and Google Cloud AI services.
Experience in deploying AI applications into production environments.
Skill Requirements
Generative AI
Google AI Stack
Agent AI Engineering
RAG & Knowledge Systems
AI Evaluation & Testing
Programming & Engineering
Cloud & DevOps
Other Requirements
Education & Experience
Education
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.Experience
2–4+ years in AI/ML or Generative AI solutions.
Hands-on experience with Gemini and Google Cloud AI services.
Experience in deploying AI applications into production environments.