We are seeking a Senior Distributed Systems & ML Engineer to design and build scalable distributed systems, Big Data pipelines, and ML/Generative AI services. This role will contribute to architecture decisions, integrate AI solutions into production, and mentor engineering teams while ensuring high-quality, production-ready code.

Key Responsibilities

Design, implement, and maintain scalable distributed systems, data pipelines, and ML services.
Participate in system architecture discussions and shape production system design decisions.
Build and optimize microservices and real-time inferencing solutions powering AI Agents.
Collaborate with cross-functional teams to integrate Big Data and Generative AI solutions into platforms such as Lakehouse, Streaming Services, and ETL Pipelines.
Write high-quality, production-ready code and engage in design reviews, code reviews, and testing.
Mentor junior engineers and contribute to engineering best practices.

Requirements

Degree in Computer Science, Mathematics, or a related field.
5+ years of experience across the full software development lifecycle (SDLC) including design, coding, testing, deployment, and operations.
3+ years of experience with distributed Big Data systems such as PySpark, Kafka, Lakehouse, Debezium, Druid, or Glue.
Hands-on experience delivering ML or Generative AI solutions such as RAG, AI Agents, or LLM fine-tuning in production.
Experience deploying large-scale systems on cloud platforms such as AWS, Azure, or GCP.
Strong problem-solving skills with the ability to deliver in fast-paced, collaborative environments.

Preferred Qualifications

MS in Computer Science, Machine Learning, or a related field.
Experience with Graph ML such as GNNs or Graph RAG.
Advanced experience in Generative AI such as RAG, Knowledge Bases, or AI Agents.

Senior Software Engineer-Big Data, Generative AI