Principal Engineer, Python fullstack (React+Genai)

REQUIREMENTS:

• Total experience 11+ years.
• Should have 10+ years of experience in software engineering, with strong depth in Python and modern frontend frameworks (React).
• Should have proven experience architecting and delivering production-grade Generative AI applications at scale.
• Design solutions and implement ML, generative AI and agentic AI models and algorithms, utilizing state-of-the-art algorithms.
• Should be able to drive backend deployment, security reviews, and QA pipelines, coordinate integration of RAG APIs and vector DB pipelines  
• Should be able to work on integrating cloud with AI algorithms and On premises AI algorithms.
• Optimize existing AI models for improved performance, scalability, and efficiency. 
• Should be able to develop and maintain AI pipelines, including data pre-processing, feature extraction, model training, and evaluation.
• Should be able to drive the team to build AI products and solutions, working in an agile methodology   Manage delivery across pods building scalable AI and API services
• Should have deep understanding of LLM integration patterns, RAG systems, and AI-driven UX design.
• Should have experience in Datarobot for architecting and building GenAI Solutions, RAG Agents and Deployment  
• Must have experience defining technical strategy and influencing architecture across teams or pods.
• Should have hands-on experience with cloud platforms (AWS, Azure, or GCP) and distributed systems.
• Should have strong grasp of security, privacy, and governance considerations for enterprise AI.
• Must have ability to translate ambiguous business problems into durable technical architectures.
• Should have excellent communication skills, with the ability to influence senior stakeholders and technical leadership.

RESPONSIBILITIES:

• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Design scalable, secure, and cost-efficient backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.
• Promote use of code quality agents and modern CI/CD practices.
• Collaborate with the Product Manager/Architect to define deliverables and technical strategy. 
• Drive the integration of AI/ML capabilities into products using market trending libraries.  
• Define frontend architecture and UX patterns for AI-native applications, including conversational interfaces, copilots, and intelligent dashboards.
•  Lead the design and implementation of complex GenAI workflows that combine LLMs, tools, APIs, structured data, and user context.
• Troubleshoot and resolve issues related to AI models and implementations.   Create and maintain documentation for AI models and their applications.  
• Establish engineering standards and best practices for prompt design, model integration, evaluation, and observability.
• Drive GenAI platformisation building reusable components, SDKs, and frameworks used across multiple teams or products.
• Partner with product, design, data, and business leaders to translate strategic objectives into scalable technical solutions.
• Review critical designs and codebases, unblock teams on complex technical challenges, and raise the overall engineering bar.
• Lead technical discovery and solutioning for high-impact initiatives, including client or executive-facing workshops when required.
• Ensure enterprise readiness: security, privacy, compliance, governance, and responsible AI practices.
•  Use AI-assisted development tools (e.g., Copilot, Claude Code) to accelerate delivery while maintaining production-grade quality.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the client’s requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.