Description

Key Responsibilities

• Design and develop AI-powered applications using LLMs and Agentic AI frameworks.
• Build multi-agent workflows using LangChain, LangGraph, and Google ADK.
• Develop scalable RAG-based applications with Vector Databases.
• Integrate enterprise systems using REST APIs, Kafka, and cloud services.
• Build reusable AI platform components for prompt orchestration, agent frameworks, and AI workflows.
• Develop production-ready AI services using Python, FastAPI, Docker, and Kubernetes.
• Implement monitoring, logging, evaluation, and governance for AI applications.
• Build automated CI/CD pipelines and deploy applications in GCP or AWS.
• Work closely with cross-functional teams to deliver enterprise AI solutions.
• Mentor developers and promote AI-first engineering best practices.

<.>Technical Skills

• Python
• Google ADK
• LangChain
• LangGraph
• ClientP / FastClientP
• Vertex AI / Gemini
• AWS Bedrock
• OpenAI APIs
• RAG
• Agentic AI
• FastAPI
• AsyncIO
• Kafka
• GCP Pub/Sub
• Docker
• Kubernetes
• GitHub Actions
• Cloud Build
• Terraform
• PostgreSQL
• MongoDB
• Firestore
• Redis
• Vector Databases
• OpenTelemetry
• Grafana

Key Skills

Education

Bachelor's degree