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We are seeking an experienced LLM & Agentic Systems Engineer to join our AI squad at our company. This role blends deep hands-on engineering with architectural responsibility and client-facing advisory work. You will design, build, and operate production-grade LLM and multi-agent systems, working on both greenfield initiatives and the evolution of existing GenAI platforms. You will play a key role in shaping technical direction, best practices, and delivery standards across the GenAI practice.
Key Responsibilities
GenAI Development & Implementation
Build end-to-end GenAI solutions from POC through production deployment
Design and implement backend microservices architectures for GenAI applications using Python
Design, implement, and maintain production-grade Python services with a focus on code quality, performance, and reliability
Architect and develop multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs across complex systems
Evaluate and improve system performance, scalability, reliabililty, and cost efficiency
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders Provide strategic technical guidance on GenAI adoption and system design
Cloud & Platform Ownership
Deploy and manage GenAI systems across GCP, Azure, and AWS Leverage cloud-native AI services (Vertex AI, Azure OpenAI, SageMaker, etc.) Own production environments, monitoring, and operational excellence
Continuous Learning & Practice Development
Evaluate emerging GenAI models, frameworks, and techniques Define and refine best practices for GenAI system development and deployment Contribute to internal accelerators, methodologies, and knowledge sharing.