Staff GenAI Engineer at Sia

Key Responsibilities

• →Lead the architecture, design, and development of scalable backend systems integrating machine learning and Generative AI models into production-grade applications.
• →Drive end-to-end delivery of GenAI solutions, including LLM-based systems, RAG architectures, and agentic workflows, from experimentation to production.
• →Design and implement agentic AI systems enabling multi-step reasoning, tool calling, memory management, and orchestration.
• →Apply a strong understanding of machine learning techniques to solution design and implementation.
• →Collaborate closely with data scientists to train, fine-tune, evaluate, and deploy ML/AI models, ensuring reliability and performance at scale.
• →Work with structured and unstructured data sources, designing efficient data pipelines and storage strategies.
• →Lead development of backend microservices and APIs supporting AI-driven applications.
• →Ensure production readiness of AI systems, including performance optimization, monitoring, cost control, and security.
• →Define cloud-native deployment strategies for AI solutions on AWS, Azure, and GCP.
• →Establish containerized deployment standards using Docker and Kubernetes across development and production environments.
• →Oversee data architecture, performance, and integrity across SQL and NoSQL databases.
• →Implement monitoring and logging frameworks to ensure reliability, observability, and operational excellence of AI systems.
• →Lead the development of AI-powered SaaS products within the Heka.ai platforms.
• →Tactical & cross-team leadership
• →Be a DRI for major architectural initiatives and blueprints; own design docs and migration plans.
• →Maintain ownership of triage and incident prioritization; advocate severity/priority to stakeholders.
• →Serve as a maintainer/owner for multiple critical repositories, tech stacks, or services.
• →Mentor engineers formally; grow others via code reviews, pairing, and career coaching.
• →Break down large efforts into epics and MVCs; coordinate cross-team delivery.
• →Facilitate or lead working groups for cross-cutting initiatives.
• →Represent your group to leadership: engineering allocation, reliability status, and iteration health.
• →Participate in hiring: design interviews, assess candidates, and recommend bias-reduction improvements.
• →Participate in Diversity, Inclusion & Belonging initiatives and mentorship programs.