Principal Engineer - Machine Learning

Lead architecture and technical strategy for core backend services of AI/ML Agentic Platform focusing on reasoning-driven agents and multi-agent orchestration.

Own design and implementation of scalable stateful dialog management, multi-agent communication protocols, and cloud-native microservices migration.

Drive LLM performance optimizations, enterprise integrations (vector DBs, RAG), and set engineering standards while mentoring senior engineers.

12–18 years of software engineering and machine learning system development experience with scalable enterprise backend systems.

Proficiency in Java and Python with experience in agentic orchestration frameworks (e.g., LangChain, LangGraph) and workflow engines (e.g., Temporal, Airflow).

Strong expertise in distributed systems: event-driven architectures, microservices, Kubernetes, Kafka, AWS cloud, and mixed databases (PostgreSQL, Vector DBs).

Work Experience Required: 12–18 years

Experienced leader capable of defining long-term platform roadmaps aligned to complex AI and business goals and influencing cross-functional engineering teams.

Deep domain expertise in AI-driven planning, multi-agent workflows, and backend system scalability at enterprise scale.

Technical mentor with a track record of elevating engineering rigor, handling ambiguity, and driving continuous technical innovation.