Lead Full Stack Engineer - AI Platform Team
Lead Full Stack Engineer - AI Platform Team
Posted 3 days ago
SENIORITY
Manager
About the role
- Lead the architecture and development of scalable full-stack solutions for agent orchestration, execution, evaluation, and monitoring· Build reusable capabilities for agent lifecycle management, context and memory, tool integration, model and prompt configuration, secure sandbox execution, and workflow orchestration· Develop intuitive experiences for building, testing, orchestrating, and managing AI agents and workflows· Integrate LLMs, AI agents, enterprise tools, and external systems into reliable production-grade solutions with appropriate guardrails· Build APIs, SDKs, platform services, and developer tools that enable teams to create, test, deploy, and operate intelligent agents· Develop evaluation and observability capabilities including testing, quality metrics, tracing, monitoring, dashboards, and debugging· Ensure solutions meet enterprise standards for security, governance, privacy, reliability, and auditability· Partner with Product, UX, Data Science, Architecture, and engineering teams to define and deliver platform capabilities· Drive scalability, resiliency, performance, and cost efficiency across cloud-native systems· Provide technical direction, mentor engineers, and establish engineering standards for AI/ML and agentic systems Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
- 4-year degree or equivalent experience 7+ years of full stack software engineering experience including technical leadership of complex systems and initiatives
- Strong programming skills in Java, Kotlin, Go, or PythonStrong experience building end-to-end applications across backend services/APIs and modern frontend technologies such as React and TypeScriptExperience building production AI/ML or GenAI applications using LLMs, agents, or agentic workflows
- Strong experience designing scalable distributed systems, APIs, and microservices architectures
- Deep understanding of system design, scalability, reliability, security, and observability
- Experience with containers, Kubernetes, CI/CD, and cloud-native development
- Experience with agent orchestration, tool calling, prompt management, context management, memory, and multi-agent systems
- Experience building evaluation frameworks for LLMs or AI agents
- Experience with secure sandboxing or isolated execution environments for AI agents
- Knowledge of AI tracing, observability, monitoring, and debugging
- Experience with RAG, vector databases, semantic search, embeddings, or model gateways
- Experience developing platform APIs, SDKs, or reusable developer tooling
- Understanding of Responsible AI, governance, guardrails, security, and privacy
- Experience with GCP, AWS, or Azure cloud
- Demonstrated ability to lead technical initiatives, mentor engineers, and influence architecture across teams
- Self-driven and results-oriented, with strong ownership, sound judgment, and the ability to move quickly while maintaining high technical standards
- Collaborative team player with a commitment to continuous learning, knowledge sharing, and building reliable AI-powered applications that create business value
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