Director of Software Development India, Alexa Ambient Computing Technologies

Interested in shaping the future of conversational and ambient AI at massive scale Join the Alexa Ambient Computing Technologies (AACT) team. AACTs mission is to design build and operate the core horizontal services that power Alexa as the worlds 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 were 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.
Were seeking a Director of Software Development to own all India-based charters and teams. This role will manage AACTs 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 thats 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.


Bachelors 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.


Masters 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:
oAI 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.
oAI 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).
oDriving 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.
oCost 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.
oTalent 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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