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Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies .Contribute to a culture of innovation by experimenting, prototyping, and scaling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.).