AI Architect
INR 2500K-4500K (estimate) Senior-level Contract Full Time
Tasks
- Architect ML systems using deep learning models
- Architect data platforms using medallion architecture
- Architect distributed systems for AI workloads
- Architect enterprise agentic AI frameworks
- Architect memory layers using vector databases
- Architect semantic caching for LLM cost reduction
- Build context modeling frameworks
- Build embeddings pipelines
- Build evaluation harnesses and hallucination detection
- Containerize with Docker and Kubernetes
- Define LLMOps evaluation and governance
- Define MLOps and CI CD pipelines
- Define agent communication and task handoff
- Deploy hybrid and on prem under compliance constraints
- Deploy secure LLMs across on prem and cloud
- Design agentic AI system patterns
- Design and implement RAG pipelines
- Design cloud native AI on Azure and AWS
- Design container and cloud native AI deployments
- Design data lakehouse with Delta tables and ACID
- Design dimensional modeling for analytics
- Design fine-tuning pipelines
- Design relational and NoSQL data models
- Design scalable AI infrastructure for model serving
- Design time series forecasting and anomaly detection
- Ensure data governance privacy compliance and responsible AI
- Govern multi tenant data platforms
- Implement CI/CD for ML pipelines
- Implement Kafka based streaming ingestion
- Implement data mesh and federated patterns
- Implement monitoring and observability
- Implement vector databases and semantic search
- Integrate DevSecOps
- Manage metadata, lineage, and data quality
- Manage releases with Helm
- Model knowledge graphs using Neo4j
- Orchestrate prompts and guardrails
- Perform schema evolution and versioning
- Predict and control token usage
- Select high reasoning and worker models
- Set explainability auditability and guardrail standards
- Use Infrastructure as Code with Terraform
Perks/Benefits
- N/A
Skills/Tech-stack
ACID transactions | AI microservices | AWS | Agent Orchestration | Agentic AI | Airflow | Anomaly Detection | Apache Druid | Apache Spark | Auditability | Autogen | Azure | Batch Processing | CI/CD | CNN | Cloud Native | Containerization | CrewAI | Data Governance | Data Lineage | Data Quality | Data mesh | Delta Lake | Delta Live Tables | Delta Live) | DevSecOps | Dimensional Modeling | Distributed Systems | Docker | Dremio | Embeddings | Evaluation Harness | Explainability | Faiss | Federated data | Fine Tuning | Graph RAG | Guardrails | Hallucination detection | Helm | Human-in-the-loop | Infrastructure as Code | Kafka | Knowledge graph | Kubeflow Pipelines | Kubernetes | LLMOps | LSTM | Langchain | Langgraph | Llamaindex | LoRA | MLOps | Medallion Architecture | Metadata Management | Milvus | Model Context Protocol | Model Serving | MongoDB | Multi-Agent | Multi-agent orchestration | Multi-tenancy | Neo4j | Observability | Operators | PEFT | Pinecone | PostgreSQL | Privacy Compliance | Prompt Guardrails | Prompt orchestration) | PyTorch | RAG Hybrid | Responsible AI | Retrieval-Augmented Generation | Schema evolution | Scikit-learn | Semantic Caching | Semantic Search | Series forecasting | Streaming processing | Telemetry | Telemetry data | TensorFlow | Terraform | The Loop | Time Series | Time Series Forecasting | Tracing | Transformer | Vector Database | Vector Search | XGBoost | “as-code”
Roles
AI | AI Architect | Architect | Data Architect | Learning Architect | Machine Learning Architect
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