Amazon opened its virtual doors in 1995 and strives to be the world’s most customer-centric company, where customers can find and discover anything they might want to buy online. Amazon Logistics (AMZL) is looking to hire an experienced, innovative, hands-on, and customer-obsessed Sr. AI Integration Engineer to identify and evaluate the proper use cases for advanced technology within the AMZL roadmap. The successful candidate will be a member of the Amazon Logistics Innovation Engineering team and will be responsible for defining where advanced systems can create the highest value in AMZL Delivery Stations, bridging the gap between emerging technologies and real operational needs. This role requires experienced and entrepreneurial-minded individuals with combined advanced technology, AI, process engineering, and analytical skills. This individual will directly influence the Amazon last mile roadmap by identifying the right use cases and partnering with teams across the company to improve safety, productivity, and the associate experience in our delivery network.
Key job responsibilities
- Identify, assess, and prioritize advanced technology use cases within AMZL Delivery Stations by analyzing process paths, ergonomic challenges, and key gaps,
- Own the integration roadmap for AMZL, defining a 3–5-year strategy aligned with the broader portfolio,
- Evaluate technology providers and platforms, conducting technical due diligence and benchmarking against operational requirements,
- Author white papers and business cases for deployment initiatives, quantifying ROI, safety improvements, and associate experience impact,
- Influence technical and business decisions through data-driven contributions based on pilot results, simulation outputs, and technology validation plans,
- Partner with providers, Mechanical, Controls and Software teams to define integration requirements (gripping, navigation, perception, task planning) for DS environments,
- Partner with simulation and digital twin teams to model performance in target process paths before physical deployment,
- Lead the scalability assessment for technologies, working with teams across the company to define path-to-scale economics,
A day in the life
You will shape the future of advanced technology in AMZL. A typical day includes visiting Delivery Stations to identify opportunities, conducting technical deep-dives with providers, running simulations to model task feasibility, and presenting pilot business cases to leadership. You will define proof-of-concept requirements, design validation criteria with cross-functional teams, and demonstrate operational, safety, and cost benefits through data.
About the team
We are a diverse team that works collaboratively to solve customer problems with innovative solutions. We prioritize empowering our employees to maintain work/life harmony. The team works with advanced technologies to bring transformative capabilities into AMZL. You will balance writing strategic business cases, evaluating emerging physical AI platforms, and understanding the interactions that will define the future of last-mile logistics.
- Speak, write, and read fluently in English
- Bachelor's degree or above in robotics, mechanical/mechatronics engineering, systems engineering or related field
- Experience designing complex systems for automation in logistics or manufacturing, or experience with product development in automotive, aerospace, automation equipment or related field
- Experience in robotics design, automation systems development, control systems design, or related product development
- Experience performing complex business case analysis to justify technical decisions and presenting the justification to management in a high-level review
- Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience in technical support
- Experience working with or evaluating AI systems
- Experience with automation and any version control tools, or experience demonstrating software engineering skills in a previous intership, work experience, coding competitions, or publications and experience troubleshooting and debugging technical systems
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
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