AI Systems Architect

16 hours ago

Nashik, Maharashtra, India beBeeArtificial Full time ₹ 18,00,000 - ₹ 21,00,000

Job Description

We are seeking a highly skilled Artificial Intelligence Engineer to lead the design, deployment, and maintenance of production-grade AI applications.

Key Responsibilities:

  • Design and implement large language model (LLM)-powered agents and natural language processing (NLP) solutions tailored to business needs.
  • Develop multi-agent and multi-modal AI applications/frameworks, ensuring interactivity, latency optimization, failover, and usability.
  • Apply advanced design principles for structured outputs, tool usage, speculative decoding, abstract syntax tree (AST)-code retriever augmented generator (RAG), streaming, and async/sync processing.

Hands-on Coding & Development

As an experienced Python developer, you will write, test, and maintain clean, scalable, and efficient code for LLMs and AI agents. You will also implement fine-tuning, embeddings, and prompt engineering with a focus on cost, latency, and accuracy. Integration with vector databases such as Milvus, Qdrant, ChromaDB, CosmosDB, and MongoDB is also essential.

Performance & Monitoring

You will be responsible for monitoring and optimizing LLM agents for latency, scalability, robustness, and explainability. This includes implementing observability and guardrails strategies for enterprise-safe AI deployments, handling model drift, token consumption optimization, and error recovery mechanisms.

Research & Innovation

As a researcher and innovator, you will stay ahead of academic and industry trends in agentic AI, multimodal AI, orchestration frameworks, and evaluation methodologies. You will read, interpret, and implement AI/Agent research papers into practical production-ready solutions, experiment with new AI orchestration tools, evaluation frameworks, and observability platforms.

Debugging & Issue Resolution

You will diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks. Advanced debugging techniques will be applied to troubleshoot deployment errors, data inconsistencies, and unexpected agent behaviors.

Required Skills & Experience

The ideal candidate should have 5-9 years of total experience, with 4+ years in NLP, CV, and LLMs. Strong expertise in GenAI, LLMs, RAG pipelines, embeddings, and vector databases is required. Proficiency in Python with strong debugging and system design skills is essential. Hands-on experience with agentic AI frameworks such as LangChain Agents, AutoGen, CrewAI, Temporal, DSPy is also necessary. A proven record of production-grade AI deployments is a must.

Cloud Experience: Azure (preferred), AWS, or GCP

Knowledge of AI Orchestration, Evaluation, Guardrails, and Observability Tools

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