Back End Developer

About the Role

We are looking for a SSDE Python ML 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 hands-on engineers who enjoy building production-grade AI systems that directly drive business outcomes.

What Youll Be Doing

Agentic & AI Systems Development

• Design and deploy intelligent, agent-driven systems that autonomously solve complex business problems
• Engineer collaborative multi-agent frameworks capable of coordinated reasoning and action
• Build and extend MCP-based infrastructure for secure, context-aware agent and tool interactions

Human-in-the-Loop AI

• Develop workflows combining agent autonomy with human oversight
• Implement continuous learning via feedback loops (e.g., RLHF, in-context correction)

AI/ML Engineering

• Build, fine-tune, train, and evaluate ML and deep-learning models using PyTorch and TensorFlow
• Work with multimodal data pipelines (text, images, structured data)
• Integrate models into production via APIs, inference pipelines, and monitoring systems

Engineering Excellence

• Follow best practices using Git, testing frameworks, and CI/CD pipelines
• Document system architecture, design decisions, and trade-offs
• Stay current with AI research and apply relevant advancements to product development

What Were Looking For

Core Technical Skills

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

Bonus Skills (Good to Have)

• Experience designing goal-oriented agentic systems and multi-agent coordination workflows
• Exposure to LangChain, LangGraph, AutoGen, Google ADK, or similar frameworks
• Knowledge of secure agent/tool communication protocols such as MCP
• Experience with RLHF and reward modeling
• Cloud platform experience.