Responsibilities

- Full-Stack Orchestration: Build and optimise RESTful services in Java (Spring Boot) to coordinate multi-agent reasoning, planning, and task execution. Develop the UI for these functionalities using a modern JS framework like Angular (Ionic).

- AI-Driven SDLC: Integrate AI productivity tools (Cursor, Claude Code, and Antigravity) into the team's daily workflow to 3-4x development speed.

- Agentic Dev Setup: Design and maintain specialised agentic development environments that automate boilerplate generation, code refactoring, and documentation for Java and Angular projects.

- Harness Engineering: Build and deploy evaluation and safety harnesses to benchmark agent-generated code against security standards, performance metrics, and functional unit tests.

- Context Engineering: Architect advanced RAG and state management systems that provide agents with accurate project-level context, ensuring high-fidelity code generation and minimising token hallucinations.

- System Reliability: Ensure agentic workflows meet production standards for scalability, latency, and token cost-efficiency (utilising semantic caching and prompt optimisation).





- Conduct code reviews and enforce best practices across AI and software engineering.

- Stay current with advancements in agentic AI, orchestration frameworks, and LLM infrastructure.

Requirements

- 2-5 years of experience in software engineering with hands-on exposure to AI-driven systems.

- Strong algorithmic thinking, coding skills, problem-solving skills, and systems-level reasoning.

- Understanding of multi-agent architectures, agent communication patterns, and task coordination.

- Solid understanding of SDLC, system design, and scalable backend architectures.

- Experience building and integrating RESTful APIs and UIs for AI and non-AI services.

- Familiarity with AI developer productivity tools such as Cursor, Antigravity, Claude Code, Codex or equivalent platforms.

- Strong communication and collaboration skills in fast-moving, experimental environments.

- Experience building and deploying production-grade applications end-to-end quickly using agentic AI is mandatory.

- Experience with open-source AI models and AI inference engines is a plus but not mandatory.

This job was posted by Meenal Sharma from Zenda.

📌 AI Software Engineer (Bengaluru)
🏢 zenda
📍 Bengaluru