SOFTWARE ENGINEER (BACKEND) – PYTHON - ADA
TechnoIogy@IA
Location
🇮🇳 Bengaluru, India
Type
full_time
Salary
Undisclosed
Posted
11h ago
Job Description
About Impact Analytics Impact Analytics is an agentic-first AI software company transforming retail merchandising through cutting-edge AI, LLMs, and Generative AI technologies. As a fast-growing Series D company with deployments across five continents, it is building both industry-leading merchandising solutions and foundational AI agents that are redefining how retail decisions are made. What makes Impact Analytics unique is its combination of deep retail domain expertise, strong innovation culture, and global presence. It is one of the few India-born AI companies recognized globally by organizations like Fortune, Gartner, and the Inc. 5000. For candidates looking to work on next-generation AI products with global scale and real-world impact, Impact Analytics is an exciting place to build your career. Here’s a link to our website: www.impactanalytics.co. The impact that you will be making We are seeking a Python Engineer who is committed not merely to functional code, but to the underlying quality and craftsmanship of software design. Our backend services form the foundation of an AI-native SaaS platform relied upon daily by ML and data teams for extension and development. The APIs you develop will not be peripheral components; they will serve as the core infrastructure upon which the broader team builds. Thoughtful, well-engineered contributions from you will enhance the effectiveness of the entire team, and the impact of your work will be felt by retailers across five continents. What we value most is a strong foundation in Python and a genuine enthusiasm for continued learning, the kind of individual inclined to independently develop a proof of concept. What This Role Entails • Design, build, and maintain backend services and APIs using Python and FastAPI, including data models and system integrations, with full ownership of the code you produce. • Deploy and manage services on Google Cloud Platform, including Cloud Run, GKE, Cloud SQL, GCS, and Pub/Sub. Prior experience with these specific tools is not required; you will receive the support and mentorship needed to develop proficiency. • Contribute to a culture of engineering excellence through constructive code reviews, thorough testing practices, and clear, well-maintained documentation. • Collaborate closely with frontend and ML engineers to deliver end-to-end features, working across functions rather than in isolation. • Maintain high standards of code quality, ensuring all merges are properly tested and free of undocumented or unclear logic, in order to minimize technical debt and future production issues. • Take initiative in exploring new tools, technologies, and approaches. Team members are encouraged to prototype and propose improvements, with the strongest ideas adopted regardless of their source. What Lands You In This Role • 1–3 years of professional experience in Python development, with hands-on exposure to backend services using FastAPI. Candidates with experience in Flask or Django and a willingness to adopt FastAPI are also encouraged to apply. • A genuine commitment to code quality, thoughtful design, and long-term maintainability, rather than a narrow focus on immediate functionality. • Demonstrated experience designing and consuming RESTful APIs, along with working knowledge of relational and/or NoSQL databases. • Some cloud experience is required. Our infrastructure runs on Google Cloud Platform (Cloud Run, GKE, Cloud SQL, GCS, and Pub/Sub), so prior experience deploying and operating services on GCP is an advantage. Candidates with equivalent experience on AWS or Azure are also welcome, as the underlying concepts are transferable. • Strong foundation in core engineering practices, including version control (Git), automated testing, CI/CD pipelines, and an appreciation for the value of code reviews. • Familiarity with Docker and containerized environments, along with an understanding of secure and scalable service design principles. • An affinity for leveraging AI tools to enhance the efficiency and quality of engineering work, or a strong interest in developing this capability.