Job Summary
AI Engineer Role Overview We are seeking experienced professionals to design, develop, and deploy Agentic AI solutions integrated with Google Cloud Platform (GCP) Big Data ecosystems. The role involves building LLM-powered multi-agent systems, implementing Retrieval-Augmented Generation (RAG) pipelines, developing scalable backend services, and delivering robust enterprise-grade AI applications on Google Cloud. Key Responsibilities • Design and develop Agentic AI workflows using enterprise-grade frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar platforms. • Build and orchestrate multi-agent systems for reasoning, planning, task decomposition, and tool execution. • Develop Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search techniques. • Design, build, and optimize scalable AI applications using Python and modern LLM frameworks. • Develop RESTful APIs and microservices using FastAPI, Flask, or similar backend frameworks. • Fine-tune and customize Large Language Models using LoRA, PEFT, QLoRA, and related techniques where required. • Integrate AI solutions with GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Functions, and Vertex AI or similar cloud exposure is mandatory. • Deploy, monitor, and manage AI/ML models on Vertex AI or similar platforms. • Build data processing and feature engineering pipelines for AI applications. • Perform prompt engineering, output evaluation, guardrail implementation, and hallucination mitigation. • Implement observability, logging, monitoring, and performance optimization for AI workloads usisng tools like Dynatrace or any evaluation framework like langsmith. • Containerize applications using Docker and support deployments on Kubernetes (GKE) environments. • Collaborate closely with Data Engineers, Platform Teams, Product Owners, and Business Stakeholders. • Ensure performance, scalability, reliability, security, and maintainability of AI solutions throughout their lifecycle.
Key Responsibilities
2. To support as an Subject Matter Expert
3. To ensure knowledge up-gradation and work with new technologies so that the solution is current and meets quality standards and the client requirements
4. Ensuring a sufficient pool of skilled professionals in the designated technology, through activities such as conducting interviews, providing training sessions and offering mentorship.
5. To gather specifications and deliver solutions to the client organization based on understanding of a domain or technology.
6. To support competency development with envisioning and articulating propositions â building collaterals/ whitepaper creation, market trend analysis etc.
7. To recommend client value creation initiatives and implement industry best practices (on specific technology/product)