Key Responsibilities

- Lead the design, development, and deployment of GenAI solutions, including LLM integration, prompt engineering, RAG systems, and domain-specific model customization.

- Evaluate emerging AI capabilities and prototype innovative solutions to accelerate business transformation. Drive experimentation frameworks that validate model performance, user experience impact, and production feasibility.

- Architect cloud-native applications capable of handling large-scale, high-availability workloads.

- Oversee performance optimization, distributed processing, caching strategies, and operational monitoring.

- Ensure secure, compliant, and resilient engineering practices aligned with enterprise standards.

- Design and evolve microservices architectures using best practices such as domain-driven design, event-driven patterns, and API-first development.

- Implement robust interservice communication (REST, gRPC, messaging) and reliability patterns (circuit breakers, rate limiting).

- Guide engineers on scaling, testing, and maintaining distributed services.

- Mentor engineering and data science teams in contemporary AI, GenAI adoption, and architectural excellence.





- Translate business goals into actionable engineering roadmaps and AI solution blueprints.

- Define coding standards, architecture guidelines, model governance, and delivery best practices.

- Collaborate closely with product, security, and platform teams to align AI solutions with enterprise strategy.

Qualifications

- 12-14 years of software engineering experience, including significant leadership in AI/ML and GenAI initiatives.

- Expertise in LLMs, embeddings, RAG systems, model finetuning, and GenAI frameworks (LangChain, LlamaIndex, Hugging Face, etc.).

- Strong proficiency in Python plus enterprise languages (Java/Scala/Go).

- Experience building scalable cloud-native systems (AWS, Azure, GCP) and microservices architectures.

- Hands-on experience with Kubernetes, Docker, CI/CD pipelines, and observability tools.

- Deep understanding of MLOps practices, model lifecycle management, and production AI monitoring.

- Proven ability to deliver large-scale analytical applications and distributed data workflows.

- Strong leadership, communication, and cross-functional collaboration skills.

📌 Director (Technology Leader Application Development,GenAI,Python,Java) (Bengaluru)
🏢 VISA CONSOLIDATED SUPPORT SERVICES (INDIA
📍 Bengaluru