Advanced AI Engineer for GenAI Solutions

6 days ago

Kannur, Kerala, India beBeeGenAie Full time ₹ 1,80,00,000 - ₹ 2,40,00,000

We are seeking a seasoned AI engineer to spearhead the development of cutting-edge GenAI solutions. With expertise in Large Language Models (LLMs) and Agentic AI, you will be responsible for designing, building, fine-tuning, and deploying production-grade agents that drive real-world business outcomes.

About the Role

This is an exciting opportunity for a talented individual to join our team and contribute to shaping the future of AI engineering. As a key member of our team, you will collaborate with cross-functional groups to conceptualize, design, and implement innovative AI-powered solutions.

Key Responsibilities:

  • Develop LLM-powered agents and NLP solutions tailored to business needs, ensuring scalability, robustness, and performance.
  • Build multi-agent and multi-modal AI applications/frameworks, focusing on interactivity, latency optimization, failover, and usability.
  • Apply advanced design principles for structured outputs, tool usage, speculative decoding, AST-Code RAG, streaming, and async/sync processing.
Hands-on Coding & Development

You will write, test, and maintain clean, scalable, and efficient Python code for LLMs and AI agents. Your focus will be on implementing fine-tuning, embeddings, and prompt engineering while minimizing cost, latency, and maximizing accuracy.

  • Integrate models with vector databases (Milvus, Qdrant, ChromaDB, CosmosDB, MongoDB).
Performance & Monitoring

You will monitor and optimize LLM agents for latency, scalability, robustness, and explainability. Additionally, you will implement observability and guardrails strategies for enterprise-safe AI deployments.

  • Handle 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 also 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. Your debugging techniques will help troubleshoot deployment errors, data inconsistencies, and unexpected agent behaviors.

Required Skills & Experience

To excel in this role, you will need:

  • 5–9 years total experience, with 4+ years in NLP, CV, and LLMs.
  • Strong expertise in GenAI, LLMs, RAG pipelines, embeddings, and vector databases.
  • Proficiency in Python with strong debugging and system design skills.
  • Hands-on experience with Agentic AI frameworks (LangChain Agents, AutoGen, CrewAI, Temporal, DSPy).
  • Proven record of production-grade AI deployments (not just POCs).
  • Cloud experience: Azure (preferred), AWS, or GCP.
  • Knowledge of AI orchestration, evaluation, guardrails, and observability tools (Arize, Weights & Biases, etc.).

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