: Senior Full Stack AI Engineer

Position: Senior Full Stack AI Engineer

Experience: 6+ Years

Location: Bangalore (preferred), Hyderabad

Joining: Immediate

About the Role

We are looking for highly skilled Senior Full Stack AI Engineers who can independently design, build, and deploy AI-powered applications leveraging Large Language Models (LLMs). The ideal candidate should be equally comfortable working across the full stack, from developing scalable backend services and modern frontend applications to creating AI-driven solutions and automated testing frameworks that enable developer-led quality engineering.

This role requires hands-on expertise in LLM development, application architecture, and test automation, effectively helping organizations accelerate delivery while reducing dependency on traditional QA teams.

Key Responsibilities

- Design, develop, and deploy AI-powered applications using Large Language Models (LLMs), with experience in Claude preferred.
- Architect and build scalable full stack applications using Java, Spring Boot, ReactJS, NextJS, TypeScript, and JavaScript.
- Develop intelligent workflows utilizing AI agents, prompt engineering, retrieval-augmented generation (RAG), and model integrations.
- Create end-to-end automated test suites using Playwright, Perfecto, and other modern automation frameworks to support developer-led testing.
- Build and integrate RESTful APIs and microservices following modern architecture principles.
- Design and manage data solutions using SQL, NoSQL, and MongoDB.
- Develop event-driven applications using messaging platforms such as Kafka.




- Implement secure, scalable, and high-performance solutions using Spring Security, OAuth, and multi-threaded programming.
- Leverage AWS services including ECS, Lambda, and Step Functions to build cloud-native applications.
- Containerize and orchestrate applications using Docker and Kubernetes.
- Drive quality through TDD, JUnit, SonarQube, CI/CD pipelines, and engineering best practices.
- Collaborate with product, design, and engineering teams across global locations to build customer-centric digital products.
- Participate in Agile ceremonies and contribute to architecture, design, and technical decision-making.

Required Skills & Experience

- 5+ years of professional software engineering experience.
- Strong hands-on expertise in:
- Java, Spring Boot
- JavaScript, TypeScript
- ReactJS, NextJS
- HTML5, CSS3
- Proven experience building and integrating AI/LLM-powered solutions.
- Ability to independently develop, evaluate, and optimize LLM-based applications.
- Robust understanding of software testing, automation frameworks, and quality engineering practices.
- Experience with:
- Playwright and/or Perfecto
- SQL, NoSQL, MongoDB
- Kafka or similar messaging platforms
- Maven, Gradle, Git-based CI/CD




- REST APIs and Microservices
- AWS cloud services
- Docker and Kubernetes
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management abilities.
- Experience working in Agile and globally distributed teams.

Preferred Qualifications

- Hands-on AI practitioner with experience building production-grade AI applications.
- Experience with:
- RAG architectures
- AI Agents and workflow orchestration
- Prompt Engineering
- Model evaluation and optimization
- Claude, OpenAI, Gemini, or comparable LLM ecosystems
- Strong understanding of distributed systems and low-latency applications.
- Experience in financial services, asset management, or fintech domains.
- Expertise in microservices architecture and cloud-native design patterns.
- Experience collaborating with UX designers and frontend specialists.
- Knowledge of visualization libraries such as HighCharts, D3.js, or similar frameworks.
- Experience delivering high-quality backend and frontend features in fast-paced environments.
- Familiarity with CMS-driven platforms and enterprise digital ecosystems.

Ideal Candidate Profile A hands-on Full Stack AI Engineer who can build AI solutions from scratch, own end-to-end application delivery, and drive quality through automation rather than manual testing practices. The candidate should combine strong engineering fundamentals with practical AI implementation experience and be capable of delivering scalable enterprise-grade solutions independently.

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