Wipro
Technical Architect (Ai)
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Role overview
We are seeking a Technical Architect of AI Engineering to lead foundational infrastructure efforts and the end-to-end delivery of several concurrent AI initiatives. This is a practitioner-first leadership role for an exceptional builder who can combine deep engineering execution with programme leadership, customer influence, and team development.
You will spend approximately 80% of your time operating as an individual contributor (Hands On), shipping production code, architecting systems and conducting rigorous peer reviews, and 20% defining technical strategy, mentoring elite AI researchers and engineers, and strengthening delivery governance. The role is accountable for engineering excellence, predictable execution, and measurable business outcomes for both Wipro and its customers.
AI initiative portfolio
- Agentic AI and autonomous workflow automation
- GenAI-powered business process transformation
- AI Engineering platforms and products
- Machine Learning and Predictive Analytics solutions
- Intelligent automation and decision-support systems
- Traditional machine learning applications
Key responsibilities
System architecture & hands-on development
- Write, deploy and maintain production-grade AI systems, custom evaluation pipelines and high-performance synthetic data generation engines.
- Architect robust, scalable agentic loops, including ReAct patterns, state machines and human-in-the-loop workflows.
- Design systems that manage complex state, use context efficiently and degrade gracefully in production.
- Guide solution architecture and technology decisions for scalable, secure and resilient AI systems.
- Drive engineering excellence across development, testing, deployment, monitoring and production support.
AI programme & delivery leadership
- Own end-to-end delivery of multiple simultaneous AI/ML, GenAI and Agentic AI programmes.
- Define delivery strategy, execution plans, milestones, governance processes and success metrics.
- Drive project execution from discovery through production deployment and operationalisation.
- Manage programme risks, dependencies, budget, scope, quality and schedule.
- Establish delivery governance and reporting mechanisms across multiple customer engagements.
- Ensure predictable delivery while maintaining engineering quality and innovation standards.
- Drive adoption of best practices for AI Engineering, MLOps, LLMOps, evaluation, observability and Responsible AI.
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Technical leadership & review
- Enforce an exceptionally high engineering standard through rigorous code reviews and scalable architectural patterns.
- Bridge the gap between open-ended research and robust software engineering.
- Work closely with architects, principal engineers, data scientists, researchers and platform teams on client side.
- Review technical risks, architecture decisions, evaluation methodologies and implementation approaches.
- Evaluate emerging AI technologies and identify opportunities for customer innovation.
- Pioneer the integration of AI coding assistants and automation into CI/CD and engineering lifecycles to maximise velocity.
Customer & executive stakeholder management
- Act as the primary delivery leader for senior customer stakeholders.
- Partner with customer executives to define AI roadmaps and transformation initiatives.
- Present programme updates, business outcomes, risks and mitigation plans to customer leadership.
- Build trusted-adviser relationships with customer executives and key business stakeholders.
- Engage regularly with Wipro delivery, account, sales and practice leadership.
- Provide accurate executive-level reporting to both Wipro and customer organisations.
Team building & talent development
- Build and lead high-performing, multidisciplinary AI engineering teams.
- Develop talent through hands-on mentoring, peer review, technical coaching and clear engineering standards.
- Define the appropriate mix of engineers, researchers, data scientists, architects and platform specialists for each initiative.
- Create a culture of ownership, experimentation, learning and disciplined production delivery.
- Strengthen technical capability, succession and leadership depth across the team.
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Required technical profile
Engineering leadership
- Proven track record as a Principal AI Engineer, Staff Engineer or highly technical Architect.
- Direct experience shipping LLM-backed applications to production and managing latency, context limits and model degradation.
- Demonstrated experience leading complex, concurrent AI programmes from discovery through deployment and operationalisation.
- Ability to balance hands-on technical contribution with executive stakeholder management, delivery governance and team leadership.
Advanced AI tooling
- Deep, practical expertise using AI-first development environments and coding assistants.
- Power-user experience with tools such as Claude Code, OpenAI Codex, Cursor or Windsurf.
- Strong understanding of context-window management across multi-file codebases.
- Practical knowledge of MLOps, LLMOps, model evaluation, observability and Responsible AI.
Core engineering
- Elite-level proficiency in Python and/or TypeScript.
- Deep familiarity with modern backend architecture, containerisation using Docker, orchestration and scalable data pipelines.
- Strong intuition for evaluating AI models, working with generative APIs and building resilient systems around non-deterministic outputs.
- Experience designing, testing and operating production systems with appropriate quality, security and reliability controls.
Education
- Bachelor's degree in Computer Science, Engineering, Information Technology or a related field.
- Master's degree preferred.
Please note this will be a fixed term contract initially
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