Sr. Sw Engineer (full-stack Developer, Java, Angular / React & Genai Engineer)

Visa · Fintech · Bengaluru, India, IN

Full-Stack Developer & GenAI Engineer responsible for designing, developing, and deploying scalable web applications enhanced with Generative AI capabilities. This role involves hands-on experience with LLM frameworks, orchestration tools, prompt engineering, and agent-based architectures to improve finance business functions. The candidate will own the end-to-end lifecycle of AI features, develop GenAI workflows like RAG and agent architectures, and mentor junior engineers.

What you'd actually do

  1. Design, build, and maintain full‑stack applications using a range of front‑end and back‑end technologies.
  2. Apply at least 2+ years of hands‑on experience in Generative AI, including LLM model development, fine‑tuning, prompt engineering, evaluation workflows, and GenAI ecosystem tools.
  3. Design and implement LLM‑powered applications, AI agents, and intelligent automation solutions.
  4. Own the end‑to‑end lifecycle of AI features—from concept, design, and architecture to deployment, monitoring, and iteration.
  5. Develop GenAI workflows such as retrieval pipelines, RAG systems, orchestration graphs, and agent-based architectures.

Skills

Required

  • Full-stack engineering expertise
  • LLM frameworks
  • orchestration tools
  • prompt engineering
  • agent-based architectures
  • Generative AI
  • LLM model development
  • fine-tuning
  • evaluation workflows
  • GenAI ecosystem tools
  • AI agents
  • intelligent automation solutions
  • end-to-end lifecycle of AI features
  • AI components and agents integration
  • GenAI workflows
  • retrieval pipelines
  • RAG systems
  • orchestration graphs
  • agent-based architectures
  • automated test cases (e.g., JUnit)
  • high scalability
  • resiliency
  • observability
  • strong monitoring practices
  • fundamental front-end languages (HTML, CSS, JavaScript)
  • JavaScript frameworks (Angular, React)
  • Web Services/API Development (REST, JSON)
  • core Java
  • scripting
  • Hibernate
  • Spring Boot
  • Python
  • database technologies (MongoDB, Oracle, PostgreSQL, MySQL)
  • LangChain
  • LangGraph
  • orchestration frameworks
  • MCP (Model Context Protocol) servers
  • tool integrations
  • fine-tune LLMs
  • RAG systems with vector databases
  • backend services, APIs, and microservices (Python/Node.js)
  • cloud platforms (AWS/Azure/GCP)
  • application reliability
  • security
  • testing
  • CI/CD
  • data teams, product teams, and DevOps collaboration
  • GIT/Stash
  • Maven
  • Jenkins
  • Agile Development Techniques

Nice to have

  • Mentoring junior engineers
  • Conducting Proofs of Concept (POCs)
  • Independent solution delivery

What the JD emphasized

  • at least 2+ years of hands‑on experience in Generative AI
  • Build and optimize GenAI workflows, including retrieval pipelines, agents, and LLM-based systems.
  • Develop tools and features using LangChain, LangGraph, and other orchestration frameworks.
  • Integrate and fine-tune LLMs (OpenAI, Anthropic, Meta, Google, etc.) for custom business use cases.
  • Implement RAG (Retrieval-Augmented Generation) systems with vector databases.

Other signals

  • LLM model development
  • fine-tuning
  • prompt engineering
  • evaluation workflows
  • GenAI ecosystem tools
  • AI agents
  • intelligent automation solutions
  • end-to-end lifecycle of AI features
  • GenAI workflows
  • retrieval pipelines
  • RAG systems
  • orchestration graphs
  • agent-based architectures
  • LangChain
  • LangGraph
  • orchestration frameworks
  • integrate and fine-tune LLMs
  • RAG systems with vector databases