Data Center Engineering. Operations Facility Manager, ADC InfraOps DCEO
Plain City, Ohio, United States
Interested in shaping the future of conversational and ambient AI at massive scale? Join the Alexa Ambient Computing Technologies (AACT) team. AACT's mission is to design, build, and operate the core horizontal services that power Alexa as the world's largest IoT installation and the most capable, efficient, and trusted AI assistant. We deliver the core capabilities that allow Alexa to connect, discover, set up, manage, and interface with over 1B connected endpoints (Echo, FireTV, Smart Home, Mobile, and Metis). Our work directly impacts every Alexa+ customer interaction, and we're obsessed with making it fast, reliable, and efficient - increasingly by putting generative AI and agentic systems at the center of how we build and operate. We're seeking a Director of Software Development to own all India-based charters and teams. This role will manage AACT's charter and lead our teams based in Bangalore and Chennai consisting of SDMs, SDEs, TPMs, and SQEs. This leader will recruit and develop high-caliber leaders and individuals and will set the standard for how an AI-first engineering organization operates - where large language models, agents, and AI-assisted development are integral to strategy, execution, and day-to-day engineering. The successful candidate will demonstrate strong intellectual curiosity, sound judgment, and creativity in solving complex, ambiguous technical problems, along with the ability to lead and scale large technical teams and influence across functions to drive results through others in a highly cross-functional environment.
Key job responsibilities • Define and drive technical strategy for critical initiatives — whether that's expanding Alexa into new modalities, enabling more fluid multi-turn conversations, or evolving our inference and orchestration infrastructure to support both. • As part of the AACT Senior Leadership team, set the India sites' strategy and lead software engineering teams. • Own Operational Excellence (OE) for AACT India-based charters — accountable for the availability, latency, security, and cost efficiency of the services your teams operate, including on-call, incident response, COEs, and driving continuous operational improvements at scale. • Champion the responsible adoption of generative AI and agentic tooling across the org — in the products you ship (LLM-driven experiences, orchestration, inference) and in how your teams build (AI-assisted coding, review, testing, and operations) — while owning the quality, safety, cost, and latency tradeoffs that come with it. • Build the talent, mechanisms, and culture that let a large organization move quickly and safely with AI, raising engineering leverage and productivity without compromising customer trust or operational excellence.
• Bachelor's degree in computer science or related field. • 15+ years of software engineering experience. • 8+ years of demonstrated experience managing senior engineering managers. • Experience as a mentor, tech lead, or leading an engineering team. • Experience collaborating across multiple organizations and influencing key outcomes. • Experience as a technical leader of multiple concurrent projects, driving strategic technical decisions. • Understanding software engineering practices and best practices for the full software development life cycle including coding standards, build processes, testing, and operations.
• Master's degree in computer science or related field. • Demonstrated experience leading product and development teams, with a focus on customer service or user-facing technologies. • Experience in a lead role in bringing a product to market. • Proven track record of taking emerging technologies from research to production-ready solutions. • Familiarity with generative AI models and their application in customer interactions and process automation. • Excellent communication and stakeholder management skills. • AI Leadership Competencies -We expect a director at this level to be fluent in AI as both a product capability and an engineering multiplier. Specifically: o AI fluency and technical judgment — A working understanding of modern generative AI: LLMs, foundation models, prompting, fine-tuning/RAG, agents and tool use, evaluation, and inference optimization. Able to engage credibly with scientists and senior engineers, ask the right questions. o AI strategy and prioritization — Able to identify genuine, durable AI opportunities and to translate them into a prioritized, measurable roadmap tied to customer and business outcomes (latency, cost-per-interaction, trust). o Driving AI-assisted engineering productivity — Actively raises the leverage of the org by adopting AI-assisted development, review, testing, and operations. Sets expectations, mechanisms, and guardrails so teams use these tools effectively and consistently, and measures the impact on throughput and quality. o Cost, latency, and scale economics of AI — Understands the economics of inference at scale and drives the right tradeoffs across model selection, orchestration, caching, and infrastructure to keep experiences fast, reliable, and efficient. o Talent and culture for an AI-first org — Attracts, develops, and retains leaders and builders who thrive in an AI-native environment, and fosters a culture of experimentation, learning, and responsible innovation.
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