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 You’ll 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  Tensor Flow
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 We’re 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  Lang Chain, Lang Graph, Auto Gen, Google ADK , or similar frameworks
Knowledge of secure agent/tool communication protocols such as  MCP

Experience with  RLHF  and reward modeling
Cloud platform experience.