Responsibilities:
* Design and build AI/ML systems from scratch to production
* Develop and maintain infrastructure that supports agentic operations at scale, including context management, evaluations, and orchestration
* Build tools and utilities used by agents
* Build APIs and wrappers for AI models and systems
* Design and build an evaluation, performance, and optimization method for agent accuracy and consistency
* Build and integrate MCP-based systems, agent utilities, and chat APIs
* Implement containerization and orchestration (Docker, Kubernetes)
* Set up monitoring, logging, and alerting for AI/ML systems
* Analyze big and complex datasets
* Use best practices of testing, tracing, and observability for analyzing, debugging, and optimizing AI / ML systems
* B.Sc or above in Computer Science, Mathematics, Statistics, or equivalent
* 5+ years of hands-on experience in software engineering, working with AI products or infrastructure
* Proficient and proven experience in Python, async patterns, and multithreading for backend systems, tooling, and AI integration
* Proficient and proven experience in SQL on DWH
* Proven experience working with LLMs, LLM fine-tuning, and AI agents in working systems
* Familiarity with LangGraph, LangSmith, LangChain, Gemini, and Cursor frameworks
* Strong foundations in software engineering, infrastructure, and cloud environments
* Understanding and experience with Docker and containerized development workflows
* Experience with implementing systems that run on the cloud (preferably GCP) Nice to have
* Understanding of Big Data technologies (Spark, Kafka, Airflow)
* Knowledge of monitoring and observability tools (Prometheus, Grafana, ELK)
* Webapp development and deployment #LI-SP1


















