Principal Engineer, AI Architect

• Total experience 11+ years.
• Should have experience in software engineering, with strong depth in Python.
• Must have experience to develop microservices and APIs (Python, FastAPI, Node.js) to embed AI and deep learning models into enterprise applications.
• Should have proven experience architecting and delivering production-grade Generative AI applications at scale.
• Should have strong system design skills across backend, frontend, and AI infrastructure layers.
• Should be able to architect and implement scalable ML, Generative AI, and Agentic AI solutions (LLMs, RAG, autonomous agents) aligned with business objectives.
• Must have good experience in Enterprise Architecture & Solution Design.
• 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.
• 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.
• Should be able to leverage emerging AI research to continuously tune models, optimize codebases, and manage scalable compute resources.
• Must have experience defining technical strategy and influencing architecture across teams or pods.
• Should be able to mentor junior engineers, drive agile workflows (Jira), and partner with Product managers to define technical strategy.
• Maintain clear technical documentation and translate complex AI concepts for non-technical audiences.
• Should have strong grasp of AI Governance & Responsible AI, Multi-cloud AI platform architecture, AgentOps / GenAIOps, Knowledge Graphs & Semantic Layer Architecture.
• Should have hands-on experience with cloud platforms (AWS, Azure, or GCP) and distributed systems.
• 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.

• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Own the architecture and technical vision for AI-powered, user-facing applications built with Python, React, and Generative AI.
• Design scalable, secure, and cost-efficient backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.
• 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.
• 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.

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

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We are a Digital Product Engineering company that is scaling in a big way!

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We work at scale across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 40 countries, to be exact).

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