Principal Engineer, AI Architect

<p><strong>REQUIREMENTS:</strong></p><ul><li>Total experience 11+&#xa0;years.</li><li>Should have&#xa0;experience in software engineering, with strong depth in Python.</li><li>Must have experience to develop microservices and APIs (Python, FastAPI, Node.js) to embed AI and deep learning models into enterprise applications.</li><li>Should have proven experience architecting and delivering production-grade Generative AI applications at scale.</li><li>Should have strong system design skills across backend, frontend, and AI infrastructure layers.</li><li>Should be able to architect and implement scalable ML, Generative AI, and Agentic AI solutions (LLMs, RAG, autonomous agents) aligned with business objectives.</li><li>Must have good experience in Enterprise Architecture &amp; Solution Design.</li><li>Should be able to build robust end-to-end AI pipelines and integrate Vector databases (e.g., Pinecone, Weaviate, Milvus) for data processing and feature extraction.</li><li>Must have experience to deploy secure, production-grade hybrid and cloud AI solutions (AWS/GCP/Azure) using modern CI/CD, AI-assisted code optimization, and strict access control.</li><li>Should be able to leverage emerging AI research to continuously tune models, optimize codebases, and manage scalable compute resources.</li><li>Must have experience defining technical strategy and influencing architecture across teams or pods.</li><li>Should be able to mentor junior engineers, drive agile workflows (Jira), and partner with Product managers to define technical strategy.</li><li>Maintain clear technical documentation and translate complex AI concepts for non-technical audiences.</li><li>Should have strong grasp of AI Governance &amp; Responsible AI, Multi-cloud AI platform architecture, AgentOps / GenAIOps, Knowledge Graphs &amp; Semantic Layer Architecture.</li><li>Should have hands-on experience with cloud platforms (AWS, Azure, or GCP) and distributed systems.</li><li>Must have ability to translate ambiguous business problems into durable technical architectures.</li><li>Should have excellent communication skills, with the ability to influence senior stakeholders and technical leadership.</li></ul><p><strong>RESPONSIBILITIES:</strong></p><ul><li>Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.</li><li>Own the architecture and technical vision for AI-powered, user-facing applications built with Python, React, and Generative AI.</li><li>Design scalable, secure, and cost-efficient backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.</li><li>Define frontend architecture and UX patterns for AI-native applications, including conversational interfaces, copilots, and intelligent dashboards.</li><li>&#xa0;Lead the design and implementation of complex GenAI workflows that combine LLMs, tools, APIs, structured data, and user context.</li><li>Establish engineering standards and best practices for prompt design, model integration, evaluation, and observability.</li><li>Drive GenAI platformisation—building reusable components, SDKs, and frameworks used across multiple teams or products.</li><li>Partner with product, design, data, and business leaders to translate strategic objectives into scalable technical solutions.</li><li>Review critical designs and codebases, unblock teams on complex technical challenges, and raise the overall engineering bar.</li><li>Lead technical discovery and solutioning for high-impact initiatives, including client or executive-facing workshops when required.</li><li>Ensure enterprise readiness: security, privacy, compliance, governance, and responsible AI practices.</li><li>&#xa0;Use AI-assisted development tools (e.g., Copilot, Claude Code) to accelerate delivery while maintaining production-grade quality.</li><li>Mapping decisions with requirements and be able to translate the same to developers.</li><li>Identifying different solutions and being able to narrow down the best option that meets the client’s requirements.</li><li>Defining guidelines and benchmarks for NFR considerations during project implementation</li><li>Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers</li><li>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.</li><li>Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it</li><li>Understanding and relating technology integration scenarios and applying these learnings in projects</li><li>Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.</li><li>Carrying out POCs to make sure that suggested design/technologies meet the requirements.</li></ul>