Lead the design and development of distributed systems, data pipelines, and ML infrastructure with a focus on scalability and reliability
Own end-to-end delivery of key features and services across the full SDLCdesign, implementation, testing, deployment, and operations
Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready systems
Build and optimize scalable, real-time analytic systems powering AI Agents
Mentor junior and mid-level engineers, provide technical guidance, and promote engineering best practices
Collaborate across teams to ensure solutions are resilient, secure, and high-performing
Requirements
Degree in Computer Science, Mathematics, or a related field
8+ years of experience across the full software development lifecycle (design, coding, reviews, testing, deployment, operations)
5+ years of experience with distributed Big Data systems (e.g., PySpark, Lakehouse, Kafka, Debezium, Hudi, Druid, Flink, Spark Streaming)
Experience with sensitive or streaming data pipelines, including governance and compliance requirements
Experience with Graph technologies (e.g., GNNs)
Proven track record of delivering complex, high-impact software systems in production
Experience deploying large-scale solutions on cloud platforms (AWS, Azure, GCP)
Strong problem-solving skills and ability to excel in ambiguous environments
Preferred Qualifications
MS in Computer Science, Machine Learning, or a related discipline
Experience with Graph ML and Graph technologies (e.g., GNNs)
Hands-on experience building Generative AI solutions (RAG, AI Agents, LLM fine-tuning) in production
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Production, Manufacturing & EngineeringRole Category: EngineeringRole: Engineering - OtherEmployement Type: Full time