Position: AI / GenAI Architect (Please share some good profiles)

Overall Experience : 12+yrs

Relevant Experience: 8+Years

Location:-

Noida (Headquarters, Sector 144)

Gurugram (ASF Insignia SEZ)

Bengaluru (Pritech Park SEZ)

Hyderabad (DLF Cybercity)

Chennai (RMZ Millen ia II)

Pune (Nyati Unitree)

Notice period-Only Immediate joiner

Contract period-Nine months to 1 Year

Monthly Rate: 2 LPM

Looking for a technical candidate with Agentic AI experience and strong hands-on experience with Python.

highly skilled AI / GenAI Architect to lead the design, development, and end-to-end operationalization of our AI infrastructure. In this role, you will be the driving force behind our agent-based architecture, responsible not only for building cutting-edge GenAI agents but also for managing the "run"—ensuring robust infrastructure, seamless production maintenance, and continuous optimization. If you excel at bridging the gap between cutting-edge AI research and reliable, scalable enterprise operations (LLMOps/MLOps), this role is for you.

10+ years of experience in Software/System Architecture or Cloud Infrastructure.

3+ years of specific, hands-on experience deploying Machine Learning or Generative AI models into production.

Proven track record of managing the operational "run" of live software/AI systems.

Job Responsibilities

Architecture &

- Agent Development

System Design: Design, develop, and scale an enterprise-grade AI and agent-based architecture.

Agent Creation: Build, test, and deploy new autonomous and semi-autonomous AI agents tailored to specific business use cases (e.g., using LangChain, LlamaIndex, AutoGen, CrewAI).

Integration: Seamlessly integrate GenAI modules, Large Language Models (LLMs), Vector Databases, and Retrieval-Augmented Generation (RAG) pipelines into existing enterprise applications.

Infrastructure & "Run" Management (LLMOps)

Infrastructure Provisioning:



Provision, configure, and maintain the underlying cloud and AI infrastructure required to support LLM inference, vector storage, and agent orchestration.

Production Maintenance: Take full ownership of the "run" phase of AI implementation. Ensure production agents are highly available, scalable, and secure.

Strategy &

- Governance: Develop and implement a comprehensive strategy for the lifecycle management, versioning, and continuous maintenance of AI modules and agents in a live production environment.

CI/CD Pipeline: Build and manage automated deployment pipelines for AI models and agent updates to ensure zero-downtime deployments.

Monitoring, Evaluation &

- Refinement

Performance Tracking: Implement robust monitoring systems to track the health, latency, and throughput of production agents.

Quality &

- Safety Control: Continuously monitor outputs for model drift, accuracy degradation, bias, and hallucinations

Continuous Improvement: Establish feedback loops to refine prompts, fine-tune models, update RAG knowledge bases, and improve overall agent performance based on real-world production data.

Technical Expertise

AI/GenAI Ecosystem: Deep expertise in LLMs (OpenAI, Anthropic, open-source models like LLaMA), prompting frameworks, and agentic orchestration frameworks (LangChain, AutoGen, Semantic Kernel).

Programming: Strong proficiency in Python and relevant backend frameworks (FastAPI, Flask, etc.).

Data &

- Storage: Experience with Vector Databases (e.g., Pinecone, Weaviate, Milvus, Qdrant) and data pipelines for RAG setups.

Infrastructure &

- Cloud: Hands-on experience provisioning and managing infrastructure on AWS, GCP, or Azure (Terraform, Kubernetes, Docker).

LLMOps / MLOps: Proven experience with AI/ML monitoring and evaluation tools (e.g., LangSmith, Weights &

- Biases, TruLens, MLflow).

Architecture Pattern-Event Broker Orecherstor /SupervisorPattern

- Dashboard- Grafana

📌 AI / GenAI Architect (India)
🏢 Sparix Global
📍 India