Senior Gen AI Engineer

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.

Role and Responsibilities

Agentic AI Systems Development

• 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.

Human-in-the-Loop AI

• Develop workflows that combine agent autonomy with human oversight, enabling continuous learning through feedback loops (e.g., RLHF, in-context correction).

AI/ML Engineering

• 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.

Engineering Excellence

• 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.

Core Technical Skills

• 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.

Bonus Skills (Great 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

Job Details

• Job Category: Artificial Intelligence
• Job Type: Full Time
• Job Location: Remote
• Experience: 5 Years to 9 Years

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.