Senior Gen AI Engineer Job at NeoQuant Solutions Pvt Ltd

Senior Gen AI Engineer

NeoQuant Solutions Pvt Ltd

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Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

We are seeking a highly skilled Senior Gen-AI & AI/ML Engineer to design, build, and deploy intelligent agentic systems that solve complex, real-world problems at enterprise scale. You will work on cutting-edge AI frameworks, multimodal pipelines, MCP-based infrastructures, and agent-driven workflows that combine autonomous reasoning with human-in-the-loop learning. This role is ideal for engineers who enjoy hands-on model development, production-grade deployments, and building advanced AI capabilities that directly impact business outcomes.

Job Responsibility:

Design and deploy intelligent, agent-driven systems that autonomously solve complex business problems using advanced AI algorithms
Engineer collaborative multi-agent frameworks capable of coordinated reasoning and action for large-scale applications
Build and extend MCP-based infrastructure enabling secure, context-rich interactions between agents and external tools/APIs
Develop workflows that combine agent autonomy with human oversight, enabling continuous learning through feedback loops (e.g., RLHF, in-context correction)
Build, fine-tune, train, and evaluate ML and deep-learning models using frameworks such as PyTorch and TensorFlow
Work with multimodal data pipelines (text, images, structured data) for embedding generation, feature extraction, and downstream tasks
Integrate models into production systems via APIs, inference pipelines, and monitoring tools
Use Git, testing frameworks, and CI/CD processes to ensure high-quality, maintainable code
Document architectural decisions, trade-offs, and system behavior to support collaboration across teams
Stay updated with AI research trends and apply relevant advancements into product design

Requirements:

Strong fluency in Python and Agentic frameworks
Solid understanding of ML fundamentals: optimization, representation learning, evaluation metrics, supervised/unsupervised/generative modeling
Hands-on experience with multimodal datasets and feature pipelines
Experience deploying ML models to production, including inference optimization and monitoring
Familiarity with LLMOps/MLOps concepts: versioning, reproducibility, observability, governance
Experience: 5 Years to 9 Years

Nice to have:

Experience designing goal-oriented agentic systems and multi-agent coordination workflows
Proficiency with LangChain, LangGraph, AutoGen, Google ADK or similar agent orchestration frameworks
Knowledge of secure tool/agent communication protocols such as MCP
Exposure to reinforcement learning from human feedback (RLHF) and reward modeling
Cloud experience

Additional Information:

Job Posted:
March 06, 2026

Employment Type:

Fulltime

Work Type:

Remote work

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