About the Role

We're hiring a Software Engineer who pairs solid Java full-stack fundamentals with genuine curiosity about building AI-powered features. You'll write and review code daily, grow your craft on real production systems, and get hands-on with products that increasingly use LLMs, RAG, and agentic workflows. This is an ideal role for an early-career engineer who wants to build a strong distributed-systems and full-stack foundation while learning to develop AI native features from the ground up.

What You'll Do: Write and review code; follow and learn the team's standards of excellence. Evaluate user requests and help clarify objectives and functional requirements for new or modified programs. Design and develop software and business-process solutions based on business needs, with guidance.

Contribute to AI-powered features helping build Mutli-agent systems, LLMbacked functionality, RAG retrieval, and simple tool-using workflows under mentorship. Help with basic quality checks for AI features (test prompts, sanity checks) so behavior stays predictable. Conduct feasibility studies for current and existing applications, making decisions within defined parameters.

Focus on quality in all aspects of work and continually improve your standards. Contribute to team activities and collaborate across teams to solve problems.

Core Engineering Experience (Required): 69 years as a Full Stack Developer across Java, Web, and Mobile technologies. 6+ years in OOAD, Java EE, Web technologies, and REST APIs. Working knowledge of database technologies relational (Oracle, Azure SQL, Postgre SQL) and/or No SQL (Mongo DB, Cassandra) with exposure to mobile data synchronization and offline storage. Working knowledge of UI/Web 2.0 development (Java Script, CSS, SCSS, HTML5, AJAX, j Query, Node JS, React JS, Angular JS) with responsive, mobile-first design.



Foundational understanding of design patterns and building scalable, maintainable applications. Familiarity with application servers (Tomcat, Jetty, Reactor Netty). 2+ years with cloud platform services (Azure, GCP, or AWS) and cloud application development.

Working knowledge of automated testing: JUnit/Test NG, plus Selenium, Playwright, Cucumber, Rest-Assured, Karate; mobile testing with Appium or Espresso. Working knowledge of the full SDLC and Agile methodologies. Exposure to CI/CD with Jenkins or Git Hub Actions; Docker/Kubernetes is a plus. Familiarity with Git Hub Copilot or similar AI-assisted development tools. Ability to understand stakeholder expectations and escalate issues that may affect delivery.

AI Skills (Mandatory): AI-augmented engineering: Comfortable using AI tools (e.g., Copilot, Chat GPT/Claude code ) in daily engineering work to write, debug, and learn faster, with growing awareness of cost-aware usage.

LLM basics: Conceptual understanding of how LLM-based applications work (chatbots, Q&A;, assistants), including the basics of prompt engineering and context.

RAG awareness: Familiarity with the idea of Retrieval-Augmented Generation retrieving relevant data to ground LLM responses.

Agentic concepts: Awareness of agentic AI ideas agents using tools, memory, and multi-step workflows. AI frameworks (exposure): Hands-on exposure through projects, coursework, or POCs to an LLM framework such as Lang Chain, Lang Graph, or Google Gen AI tools.

Mandatory Skills Summary: Languages: Java 11+ Databases: My SQL / Postgre SQL / Oracle / Mongo DB / Cassandra Frontend: HTML / CSS / Java Script / React JS / Bootstrap Backend: Spring Boot / REST APIs / Microservices Automation Testing: JUnit / Selenium / Playwright / Cucumber / Jest Cloud: AWS / GCP / Azure Dev Ops: CI/CD, Git Hub, Jenkins AI: LLM basics, RAG awareness, agentic concepts, Lang Chain/Lang Graph exposure

📌 Senior Engineer Software (applied Ai) (Bengaluru)
🏢 Albertsons Companies India
📍 Bengaluru