Software Development Engineer, Amazon Pharmacy, Amazon Phamarcy
ADCI - Karnataka•2h ago
IN, KA, BengaluruOnsiteFull-timeMid Level3+ yrs exp
Top focus
Software EngineerSoftware Engineer IiSenior Software Engineer
- Join Amazon Pharmacy's Supply Chain Engineering team in Bangalore and build the systems that determine how medications reach patients. You will design and develop ML-driven supply chain technology: demand forecasting models that predict prescription volume, procurement systems that optimize purchasing under expiry and regulatory constraints, placement algorithms that position inventory across fulfillment centers
- planning systems that allocate capacity to meet patient demand. You will work at the intersection of software engineering, operations research
- machine learning. This is a founding team. You will build new systems from scratch, not maintain legacy code. You will work with large-scale datasets, ML models in production
- distributed systems that must be highly available because medication access depends on them. Pharmacy supply chains are unlike retail: demand is driven by prescriptions (not browsing), products expire, controlled substances require compliance layers
- regulations vary by state. Every system you build operates under these constraints. We are building an AI-native engineering team. You will use AI-augmented development workflows daily: code generation, automated testing, AI-assisted code review. We expect engineers who learn fast, build smart
- own their systems end-to-end from design through production operations. Key job responsibilities Key job responsibilities A. System Design & Development
- Design and build scalable, resilient services for supply chain optimization: forecasting, procurement, placement, or planning
- Develop ML-integrated systems that improve over time: learned demand models, intelligent reorder logic, placement optimization
- Write high-quality, well-tested code and participate actively in code reviews
- Implement operations research techniques in production: optimization solvers, simulation engines, probabilistic demand models, safety stock calculations
- Follow supply chain engineering best practices: backtesting against historical data, offline evaluation before deployment, experiment design for measuring real-world supply chain impact
- Build data pipelines that process large-scale pharmacy supply chain signals: prescription fills, supplier lead times, inventory positions, drug expiry dates B. Operational Ownership
- Own the systems you build end-to-end: design, development, testing, deployment, monitoring, and oncall
- Build robust observability: metrics, alarms, dashboards that surface supply chain health in real time
- Participate in oncall rotations and drive root-cause analysis for production issues
- Design for failure: implement graceful degradation, circuit breakers, and fallback strategies for mission-critical services C. Collaboration & Growth
- Partner with Applied Scientists to productionize ML models and experimentation frameworks
- Work with product managers to translate business problems into technical designs
- Collaborate across time zones with US-based teams on priorities, design reviews, and operational handoffs
- Contribute to a learning culture: share knowledge, mentor peers, and drive engineering best practices D. Innovation
- Leverage AI tools to accelerate development velocity and improve code quality
- Identify opportunities for automation and ML within your domain
- Propose and execute on technical improvements that reduce operational toil or improve system performance
- Stay current with advances in supply chain ML, optimization, and distributed systems
- 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language - Knowledge of machine learning model architecture and inference
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing
- operations experience - Bachelor's degree in computer science or equivalent - Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles
- optimization techniques Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Required skills
Machine LearningPythonSoftware DevelopmentOperations ResearchData Pipelines