1 month ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect and evolve an Agentic AI platform supporting multi-agent orchestration, RAG, and integration with enterprise microservices.
- Design and implement scalable backend systems and RESTful/gRPC APIs using Java, Spring Boot, Python, FastAPI, and Flask.
- Integrate GPT, Claude, Mistral, Gemini, and other LLMs into production backend systems.
- Build RAG pipelines using vector databases and develop agentic workflows with LangChain, LangGraph, and AutoGen.
- Lead distributed-system scalability, fault tolerance, autoscaling, monitoring, observability, latency reduction, and cost optimization.
- Build reusable AI platform components, SDKs, and internal developer tooling.
- Define LLM and agent evaluation metrics and testing frameworks for accuracy, latency, cost, reliability, and performance.
- Design secure and compliant AI systems with privacy, prompt security, auditability, and responsible-AI safeguards.
- Lead production readiness, incident response, post-mortems, and continuous improvements in resilience and deployment practices.
- Mentor developers, set coding standards, lead design reviews, and influence platform strategy and roadmap across cross-functional teams.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 11+ years of backend software development experience with Java and Spring Boot.
- 2+ years of backend experience with Python and FastAPI, Flask, or similar frameworks.
- Production-level experience building and deploying agentic AI solutions, including LLM-agent orchestration, enterprise microservice integration, and live-production troubleshooting.
- Hands-on experience implementing LLM, GenAI, and RAG systems with LangChain, LangGraph, or AutoGen.
- Experience building and integrating Model Context Protocol frameworks for tool and API interoperability.
- Strong understanding of AI orchestration and LLM integration patterns in distributed environments.
- Proven experience building and scaling distributed microservice architectures.
- Proficiency in API design, event-driven architectures, and message queues such as Kafka and RabbitMQ.
- Experience with vector databases including Pinecone, Weaviate, and FAISS and with RAG pipelines.
- Hands-on expertise with AWS, GCP, and Azure.
- Familiarity with SQL and NoSQL databases including MySQL, DynamoDB, and MongoDB.
- Experience with Docker, Kubernetes, ArgoCD, Jenkins, and GitHub Actions.
- Excellent debugging, performance optimization, and large-scale system design skills.
- Ability to provide technical and people leadership, mentor engineers, establish standards, and drive execution across multidisciplinary teams.
Benefits
- Hybrid work arrangement requiring at least three days in the office, with specific days confirmed by the hiring manager.
- Opportunity to build production Agentic AI systems and reusable platform capabilities at global payments scale.
- Opportunity to work with senior engineers, ML engineers, product leads, data teams, and security teams on platform strategy and delivery.
Tech Stack
Amazon DynamoDBApache KafkaAWSAzureDockerFastAPIFlaskGitHub ActionsGoogle Cloud PlatformGrafanaGraphQLgRPCJavaJenkinsKubernetesMongoDBMySQLPrometheusPythonRabbitMQReactSpring BootTypeScript
Categories
About Visa
Visa builds and operates a global digital payments network that connects consumers, merchants, financial institutions, and governments. It earns fees for processing card transactions and offering risk, data, and value‑added services through VisaNet and products like tokenization and tap‑to‑pay. Founded in 1958 and headquartered in Foster City, California, Visa is a public company (NYSE: V) serving clients in more than 200 countries and territories.