Staff Engineer Genai Developer

Visa · Fintech · Bengaluru, India, IN

Staff Engineer GenAI Developer role at Visa, focusing on building generative AI solutions for internal employee use cases like intent processing, RAG, agentic actions, and document summarization. The role involves technical leadership, architecture definition, hands-on development using Python and LangChain, cross-functional collaboration, mentorship, establishing best practices, agile project leadership, and ensuring responsible AI principles are followed. Requires expertise in Python, LangChain, Azure, and vector databases.

What you'd actually do

  1. Define and drive the technical vision architecture and roadmap for GenAI initiatives ensuring solutions are scalable secure and high performance to meet enterprise needs. This includes architecting core GenAI capabilities such as LLM agent orchestration retrieval augmented generation RAG pipelines prompt engineering tools and model fine tuning workflows that support advanced use cases intent understanding document summarization autonomous agents and more. You will make high level design decisions and determine the priority of which AI problems to tackle for maximum business impact.
  2. Lead the end to end development and implementation of GenAI solutions. You will not only oversee architecture but also dive into coding and prototyping critical components especially in Python or Java to integrate large language models LLMs and frameworks such as LangChain with our platforms. You will ensure that AI models including embeddings and knowledge bases for RAG are effectively used to solve real world problems for employees.
  3. Work closely with product managers data scientists and platform engineers to integrate GenAI features into existing products and workflows. As the GenAI subject matter expert you will collaborate with multiple teams across departments or regions to drive adoption of AI capabilities in high impact use cases and ensure solutions fit within the broader technology ecosystem. This includes coordinating with other engineering leaders to align GenAI efforts with the companys technology vision and product roadmap.
  4. Provide technical leadership and mentorship to the engineering team. You will guide junior and senior developers alike sharing deep expertise in AI ML and helping elevate the overall skill level of the team. This involves code reviews pair programming and advising on solution design. As a Staff Engineer you will foster an inclusive learning oriented environment and may lead micro teams or pods focused on specific product features ensuring they deliver quality results.
  5. Establish and enforce software development best practices across the GenAI team and related teams. You will create technical guidelines set coding standards and ensure robust testing code quality and documentation for all AI projects. A key part of the role is to champion engineering excellence driving the adoption of continuous integration CI code review rigor high test coverage and secure coding practices for any AI driven software. You will also ensure that all development conforms to the companys standards for security performance resiliency and compliance as expected in a mission critical enterprise environment.

Skills

Required

  • Python
  • LangChain
  • Azure cloud services
  • vector databases
  • LLM agent orchestration
  • retrieval augmented generation (RAG)
  • prompt engineering
  • model fine tuning
  • Java

Nice to have

  • product driven mindset
  • mentorship skills
  • Agile Scrum process
  • CI CD pipelines
  • Jenkins

What the JD emphasized

  • deep expertise in Python LangChain Azure cloud services and vector databases for AI
  • architecting core GenAI capabilities such as LLM agent orchestration retrieval augmented generation RAG pipelines prompt engineering tools and model fine tuning workflows
  • dive into coding and prototyping critical components especially in Python or Java
  • integrate large language models LLMs and frameworks such as LangChain
  • AI models including embeddings and knowledge bases for RAG
  • responsible AI principles
  • guardrails for AI usage
  • safe deployment of LLMs

Other signals

  • drive the development of generative AI solutions
  • technical leadership across teams
  • define and enforce best practices
  • ensure our GenAI platforms and applications are robust scalable and aligned with business needs
  • hands on leader with a deep expertise in Python LangChain Azure cloud services and vector databases for AI