Full Stack Engineer
Posted Updated
Summary
Full-stack engineer (2-4 yrs) building Java/Spring Boot REST services and Angular (Ionic) UIs that orchestrate multi-agent AI systems, plus AI-driven dev workflows (Cursor, Claude Code), evaluation/safety harnesses, and RAG context systems. Based in Kochi or Bangalore; pays up to 10 LPA.
Full-Stack Software Engineer (Agentic Systems)
Location: Kochi/Bangalore
Experience Level: 2-4 Years
Compensation: Upto 10 Lacs per annum (flexible for the right candidate with relevant experience)
Responsibilities:
- Full-Stack Orchestration: Build and optimize 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, Antigravity) into the team's daily workflow to 3–4x development speed.
- Agentic Dev Setup: Design and maintain specialized Agentic Development Environments that automate boilerplate generation, code refactoring, and documentation for Java and Angular projects.
- Harness Engineering: Build and deploy Evaluation & Safety Harnesses to benchmark agent-generated code against security standards, performance metrics, and functional unit tests.
- Context Engineering: Architect advanced RAG & State Management systems that provide agents with precise project-level context, ensuring high-fidelity code generation and minimizing token hallucinations.
- System Reliability: Ensure agentic workflows meet production standards for scalability, latency, and token cost-efficiency (utilizing semantic caching and prompt optimization).
- 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.