About the job
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. Our team builds the systems that plan, price, and orchestrate this infrastructure at scale. You'll join a team of software engineers building large-scale distributed systems, data pipelines, and ML- and agentic-powered automation, working alongside product, finance, and supply chain partners across AWS.
Responsibilities
1. Design, implement, and deploy large-scale, secure, low-latency services and data pipelines that power pricing, quoting, sourcing, and cost estimation for AWS hardware.\n2. Lead the development of ML and statistical models for cost estimation and forecasting, and drive them from prototype to production with the right accuracy, monitoring, and business guardrails.\n3. Build agentic and LLM-powered workflows that automate manual steps in quoting, sourcing, and vendor operations, including evaluation and quality controls for non-deterministic systems.\n4. Functionally decompose complex, ambiguous supply-chain problems into simple, straightforward solutions, and understand system interdependencies and limitations.\n5. Partner with Finance, procurement, and vendor-facing teams to translate business problems into technical solutions, and drive measurable impact.\n6. Share knowledge in performance, scalability, system architecture, ML/GenAI practices, and engineering best practices, and mentor engineers across the team.
Qualifications
Minimum
1. 5+ years of non-internship professional software development experience.\n2. 5+ years of programming with at least one software programming language experience.\n3. 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.\n4. Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence.\n5. Experience as a mentor, tech lead or leading an engineering team.
Preferred
1. 6+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.\n2. Master's degree in computer science or equivalent.\n3. A track record of identifying where automation or ML can replace manual effort and driving that change with measurable impact.\n4. Experience building and productionizing ML or statistical models for prediction, forecasting, or estimation (e.g. pricing, cost, demand, or time-series forecasting).\n5. Experience designing and shipping agentic or LLM-powered workflows (tool-calling agents, retrieval-augmented generation, multi-step automation), including prompt design, evaluation, and guardrails.\n6. Experience integrating foundation models (e.g. Amazon Bedrock) into backend services and measuring quality/regression of non-deterministic systems.\n7. Experience building large-scale distributed backend services and data pipelines (event-driven architectures, batch and streaming data processing).