Need REALLY STRONG CVs
Expectation from client: 80% hands on AI architect with 20% team management
experience. This person is expected to discover AI Transformation projects and
drive them to closure. Manage a small team of 3 -4 engineers based in India.
(More details in JD)
Number of Rounds: 3 (2 Technical - Internal Wipro and Client, 1 Business)
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.
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.
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.