

Search by job, company or skills

Skills: Python + Gen AI + Agentic AI
Experience: 15+yrs
Location: Greater Noida (5 Days WFO)
Job Summary
We are seeking an experienced AI Architect with deep expertise in Python, Generative AI (Gen AI), Large Language Models (LLMs), and Agentic AI frameworks to lead the design and implementation of next-generation AI solutions. The ideal candidate will be responsible for architecting scalable AI platforms, defining AI strategies, and delivering enterprise-grade solutions that leverage Gen AI, Agentic AI, machine learning, and cloud technologies.
The candidate will work closely with business stakeholders, data scientists, engineering teams, and solution architects to drive AI-led innovation and accelerate digital transformation initiatives.
Key Responsibilities
Job ID: 153322673
Skills:
Api Development, Technical Documentation, Typescript, Javascript, Pytorch, Python development, Azure, LangChain, AWS Bedrock, knowledge graphs, RAG systems, multi-agent architectures, AI agent orchestration, vector databases, cloud AI services, enterprise AI integration, Transformers, MLOps tools, Google Vertex AI, AI model performance tuning, OpenAI, LlamaIndex, Large Language Models
Skills:
AI ML, Python, Machine Learning, Pytorch
Skills:
AWS, Spring Boot, Tensorflow, MLops, Pytorch, Kubernetes, Python, Azure, Docker, scikit-learn, multi-agent systems, AWS SageMaker, R, Azure AI, microservices architecture, Google Vertex AI
Skills:
Sql, Containers, Deep Learning, Tensorflow, Hadoop, Tableau, Kafka, MLops, Data Science, Pytorch, Gcp, Natural Language Processing, Apache Spark, Machine Learning, Cloud Computing, AWS, Powerbi, Python, Kubernetes, Azure, Docker, Nlp, Llm, Ai, GenAI, CI CD, Statistics, Scikit-learn, R
Skills:
distributed caching , messaging platforms , Java, Grafana, Database Technologies, Logging, Performance Engineering, Splunk, Kibana, Datadog, Distributed Systems, Prometheus, Kubernetes, metrics, event-driven architecture, observability platforms, OpenTelemetry, Monitoring, DevOps practices, cloud-native engineering, asynchronous processing, tracing, Infrastructure as Code, alerting, AI-assisted software engineering practices