Drive the design and implementation of core platform services including API gateways, vector store integrations, RAG pipelines, and context management.
Oversee integrations with third-party tools, internal services, and infrastructure platforms to enable real-world agent execution at scale.
Guide the team in applying best practices in cloud-native development, distributed computing, observability, and security.
Manage, mentor, and grow a high-performing team of backend engineers and platform specialists.
Ensure alignment between platform capabilities and evolving needs from AI product lines and downstream applications.
Drive technical excellence through code and design reviews, system reliability practices, and collaboration across engineering functions.
Contribute to the long-term vision and strategy of how agentic workflows will operate at scale across the organization.
What Makes You A Qualified Candidate
12+ years of experience in software/platform engineering, with 3+ years in engineering management or technical leadership roles.
Proven experience building and scaling distributed systems or cloud platforms in production environments.
Strong technical background in backend development, APIs, infrastructure, or platform architecture.
Familiarity with AI/ML platforms, LLM integrations, or autonomous agent frameworks (LangChain, CrewAI, AutoGen, etc.) is highly desirable.
Solid understanding of cloud platforms (AWS, Azure, GCP), container orchestration (Kubernetes), and microservices.
Experience working with vector databases, semantic search, or data pipelines is a plus.
Strong project management skills, with a track record of delivering large cross-functional initiatives.
Excellent communication and collaboration skills, with the ability to work closely with executive stakeholders, researchers, and engineers.
Passion for building platforms that enable intelligent, autonomous behavior at scale.
What You'll Bring
A strong track record of leading platform engineering teams that build scalable, reliable systems supporting internal and external developers or AI/ML workloads.
Deep understanding of software architecture, distributed systems, and cloud-native infrastructure — with the ability to make strategic technical decisions.
Experience working at the intersection of AI and engineering, ideally supporting LLM-based products or intelligent automation platforms.
A pragmatic approach to balancing technical depth with delivery speed, especially in fast-paced, R&D-heavy environments.
Demonstrated ability to hire, mentor, and retain high-performing engineers while fostering a culture of ownership, experimentation, and accountability.
Strong cross-functional collaboration skills — able to partner effectively with product managers, researchers, infrastructure teams, and executive stakeholders.
Curiosity and drive to push the boundaries of autonomous software, and a vision for how agentic systems will shape the next generation of applications.
Excellent written and verbal communication skills, with the ability to articulate complex ideas clearly to technical and non-technical audiences.
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