GenAI professional -Agentic AI

We are Hiring GenAI professional with proven production-grade project deployment experience with strong expertise in Agentic AI.

About the Role

We are looking for a GenAI professional with strong experience in NLP, Computer Vision, and LLM-based agentic systems . In this role, you will design, build, fine-tune, and deploy production-grade LLM agents and multi-modal AI applications that solve real-world business challenges. You will play a key role in shaping agent design, orchestration, and observability , ensuring enterprise-grade scalability, robustness, and performance.

Key Responsibilities

Model & Agent Design

Conceptualize, design, and implement LLM-powered agents and NLP solutions tailored to business needs.

Build 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, AST-Code RAG, streaming, and async / sync processing .

Hands-on Coding & Development

Write, test, and maintain clean, scalable, and efficient Python code for LLMs and AI agents.

Implement fine-tuning, embeddings, and prompt engineering with a focus on cost, latency, and accuracy.

Integrate models with vector databases (Milvus, Qdrant, ChromaDB, CosmosDB, MongoDB).

Performance & Monitoring

Monitor and optimize LLM agents for latency, scalability, robustness, and explainability.

Implement observability and guardrails strategies for enterprise-safe AI deployments.

Handle model drift, token consumption optimization, and error recovery mechanisms .

Research & Innovation

Read, interpret, and implement AI / Agent research papers into practical production-ready solutions.

Stay ahead of academic and industry trends in Agentic AI, multimodal AI, orchestration frameworks, and evaluation methodologies .

Experiment with new AI orchestration tools, evaluation frameworks, and observability platforms (Arize or similar).

Debugging & Issue Resolution

Diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks .

Apply advanced debugging techniques to troubleshoot deployment errors, data inconsistencies, and unexpected agent behaviors.

Continuous Learning & Adaptability

Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies .

Contribute to a culture of innovation by experimenting, prototyping, and scaling cutting-edge AI solutions.

Required Skills & Experience

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.).