AWS AI Architect

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.

To be updated

Role - AWS AI Architect

US Locations- (Newyork City, Chicago, Miami, Dallas) – Hybrid

M = must have, P = preferred differentiator.

Key Responsibilities

• Platforms and Tools
• M1 AWS GenAI and agentic architecture
• Production Bedrock and AgentCore. Choose agent vs direct inference to resolve Artemis design decisions.
• M2 multi-agent orchestration
• Agent-as-tool, graph and swarm patterns. Build reusable Agent Factory blueprints with clear limits.
• M3 Tools and Protocols
• MCP, A2A and tool registries. Resolve enterprise connectivity, tool naming and permission decisions.
• P13 Classical ML platforms
• SageMaker registry and monitoring. Support coexistence of classical ML and GenAI on Atlas.

• Security and Data
• M4 AI identity and security
• Agent identity, OAuth, Cedar/IAM and isolation. Close credential, access and AI security control gaps.
• M5 RAG, Knowledge Bases and AI-ready data
• Own retrieval lifecycle and semantic context. Establish enterprise KB standards beyond ProServe scope.
• M6 Sensitive data protection
• Protect PII/PCI in prompts, memory and logs. Enable de-identified and synthetic data for AI/ML.
• P14 AI-assisted engineering
• Govern Claude Code, Kiro and Q Developer. Address coding-assistant leakage and code review controls.

Evidence expected
Production architecture examples showing design choices, ownership, security controls and operating lessons.

• Operations and Risk
• M7 AgentOps / LLMOps and evaluation
• Online evaluation, drift and p95/p99 latency. Close monitoring gaps with kill switches and tested fallback.
• M8 AI FinOps
• Token budgets, model routing and cost per task. Establish cost controls across Bedrock and Snowflake AI.
• M9 AI governance and regulatory alignment
• Map NIST AI RMF, ISO 42001 and model risk controls. Connect platform requirements to AI approvals.
• P15 Executive Communication
• Explain trade-offs to governance forums in English and Spanish. Support EA Council and local stakeholders.

• Enterprise Delivery
• M10 Third-party and embedded AI evaluation
• Assess data boundaries and build/buy/host options. Evaluate Cyber.AI, Archer RAG and Snowflake AI.
• M11 EA artifact authoring
• Produce RAs, Patterns, IRs, ADRs and Stage 1–3 designs. Turn AI decisions into enforceable architecture.
• M12 Operating model and enablement
• Define intake, RACI and paired knowledge transfer. Sustain Agent Factory after the ProServe handover.
• Required and preferred credentials
• Required: AWS SA Professional + current AWS AI/ML or GenAI credential. Preferred: AIGP or ISO 42001 training.

Required Certifications

1. AWS Certified Solutions Architect – Professional
2. A current AWS artificial intelligence, machine-learning, or generative AI credential
3. Preferred Qualifications
4. Previous banking or financial services experience.
5. Experience working with model-risk management teams and AI governance boards within a financial institution.
6. Experience with Amazon SageMaker model registry and monitoring capabilities.
7. Familiarity with Snowflake AI and the coexistence of classical machine learning and generative AI.
8. Experience governing AI-assisted development tools such as Claude Code, Kiro, or Amazon Q Developer.
9. IAPP Artificial Intelligence Governance Professional, or AIGP, certification.
10. ISO/IEC 42001 training or implementation experience.
11. Professional proficiency in Spanish.
12. Ability to support stakeholders located in the San Juan time zone and participate in onsite working sessions when required.

Mandatory Skills: AWS Gen AI . Experience: 8-10 Years .The expected compensation for this role ranges from $80,000 to $158,000 . Final compensation will depend on various factors, including your geographical location, minimum wage obligations, skills, and relevant experience. Based on the position, the role is also eligible for Wipro's standard benefits including a full range of medical and dental benefits options, disability insurance, paid time off (inclusive of sick leave), other paid and unpaid leave options. Applicants are advised that employment in some roles may be conditioned on successful completion of a post-offer drug screening, subject to applicable state law. Wipro provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Applications from veterans and people with disabilities are explicitly welcome. Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.