to serve as a key anchor resource for our AI/ML initiatives. This role requires strong technical expertise, the ability to build and maintain strong client relationships, and hands-on experience delivering
production-grade AI/ML/NLP solutions
. The ideal candidate must have experience working on AI systems that have gone live, proficiency in troubleshooting production issues, and deep knowledge of
RAG pipelines
and
multi-agent systems
.
Key Responsibilities
Act as the primary
technical and client-facing lead
for AI/ML projects, ensuring alignment with business goals.
Mentor and guide engineering teams while fostering a collaborative and high-performance environment.
Design, develop, and deploy advanced
AI/ML and NLP-based solutions
for enterprise-scale applications.
Fine-tune and implement
Large Language Models (LLMs)
tailored to specific business requirements.
Architect, build, and maintain
MLOps pipelines
using tools such as MLflow, Seldon, and Docker for scalable deployments.
Develop, optimize, and maintain
RAG (Retrieval-Augmented Generation) pipelines
for enterprise knowledge and search applications.
Build and orchestrate
multi-agent AI systems
ensuring reliable coordination and execution of tasks.
Support, monitor, and enhance
production-grade AI systems
to ensure performance, uptime, and reliability.
Lead AI-driven initiatives involving
document parsing, forgery detection, and intelligent automation
.
Design and deploy conversational AI solutions using
Azure Speech Services
and multi-agent orchestration frameworks.
Collaborate with cross-functional teams to transform complex business challenges into scalable AI solutions.
Stay up to date with advancements in AI/ML, integrating emerging tools and innovations into ongoing projects.
Job Type: Permanent
Pay: ₹1,800,000.00 - ₹2,600,000.00 per year
Application Question(s):
Do you have 8 years of experience in AI Engineer ?
Do you have hands-on experience working on AI/ML projects that have gone live ?
Do you have strong technical expertise in AI/ML/NLP ?
Do you have experience with RAG pipelines ?
Work Location: Remote
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