Senior AWS AI/ML & Advanced Analytics Architect

Job Description & Summary : We are looking for an exceptional, innovation-driven Senior AWS AI/ML & Advanced Analytics Architect with expertise in Data, AI & Digital Transformation practice. This is a highly specialized and strategic leadership role designed for a practitioner-turned-leader who brings 15+ years of deep, hands-on experience in architecting and delivering transformative AI/ML, Generative AI, Agentic systems, IoT, and Advanced Analytics solutions on AWS at enterprise scale.

Will be guiding clients through complex digital transformation journeys, building industry-leading solutions, and driving measurable, quantifiable ROI from cloud-native AI investments. Will advise C-suite executives, spearhead pre-sales pursuits, mentor high-performing teams, and shape the firm's AI & data go-to-market strategy on AWS.

Job Position Title: Senior AWS AI/ML & Advanced Analytics Architect

Responsibilities:

AI/ML Architecture & Delivery Leadership

• Architect, design, and govern enterprise-scale AI/ML platforms on AWS covering the full ML lifecycle — data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
• Lead hands-on delivery of production-grade ML solutions using Amazon SageMaker (Studio, Pipelines, Feature Store, Model Monitor, Canvas, JumpStart), Bedrock, Rekognition, Comprehend, Textract, Forecast, Personalize, and Fraud Detector.
• Define ML Ops frameworks including automated model versioning, CI/CD for ML, drift detection, and model governance for industries.
• Drive AI/ML ROI realization frameworks — baseline establishment, KPI definition, value tracking dashboards, and business case validation post go-live.

Generative AI & Agentic Systems

• Lead the architecture and delivery of GenAI solutions using Amazon Bedrock, foundation models (Claude, Titan, Llama, Mistral, Stable Diffusion), RAG (Retrieval-Augmented Generation) pipelines, and prompt engineering frameworks.
• Design and implement Agentic AI architectures — multi-agent orchestration, tool-use agents, ReAct agents, autonomous workflow agents — using Amazon Bedrock, Agents, Leah, LangChain, AutoGen, and CrewAI frameworks on AWS infrastructure.
• Build enterprise-grade GenAI applications including intelligent document processing, AI-powered knowledge bases, conversational AI platforms, code generation assistants, and AI-driven decision support systems.
• Establish responsible AI governance frameworks — hallucination mitigation, guardrails, explainability, bias detection, and compliance-aware GenAI deployment using Amazon Bedrock Guardrails.
• Advise clients on GenAI operating models, build-vs-buy decisions, model selection criteria, and total cost of inference optimization.

Advanced Data Analytics on AWS Cloud

• Architect modern data platforms and lakehouse architectures on AWS using S3, AWS Glue, Apache Iceberg/Delta Lake, Lake Formation, Athena, Redshift (Serverless & RA3), EMR, and AWS Glue DataBrew.
• Design and deliver real-time and batch analytics pipelines using Kinesis Data Streams, Kinesis Firehose, Apache Kafka (MSK), AWS Glue Streaming, and Apache Flink.
• Lead implementation of advanced analytics and BI layers using Amazon QuickSight (Q, embedded analytics), Grafana, and integration with third-party visualization platforms.
• Architect data mesh and data fabric frameworks aligned with organizational data governance and ownership models.
• Drive data democratization initiatives — self-service analytics, natural language querying (QuickSight Q), and data catalog adoption via AWS Glue Data Catalog and Apache Atlas.

Multi-Source Data Ingestion & Integration

• Design enterprise data ingestion architectures supporting structured, semi-structured, and unstructured data from diverse sources including:
• On-premises databases (Oracle, SQL Server, SAP, Mainframe)
• SaaS platforms (Salesforce, SAP S/4HANA, ServiceNow, Workday)
• IoT devices and edge sensors
• Streaming sources (Kafka, Kinesis, MQTT brokers)
• Third-party APIs, web scraping pipelines, and data marketplaces
• Leverage AWS native and hybrid integration services — AWS DMS, Glue, AppFlow, DataSync, Transfer Family, EventBridge, and Step Functions.
• Define data quality, lineage, cataloging, and observability standards across all ingestion pipelines using tools like Great Expectations, AWS Glue Data Quality, and Monte Carlo.

IoT Architecture & Edge Intelligence

• Architect and deliver end-to-end IoT solutions on AWS using AWS IoT Core, IoT Greengrass, IoT SiteWise, IoT TwinMaker, IoT Events, IoT Analytics, and IoT Device Management.
• Design edge-to-cloud intelligence pipelines — data capture at edge, local inference with SageMaker Edge Manager / Greengrass ML, and cloud aggregation.
• Lead industrial IoT (IIoT) engagements for manufacturing, energy, utilities, and smart infrastructure clients covering asset monitoring, predictive maintenance, OT/IT convergence, and SCADA integration
• Define IoT security architectures — device identity, certificate management, OTA updates, and zero-trust device connectivity.

Digital Twins

• Architect and deliver advanced Digital Twin solutions using AWS IoT TwinMaker, integrating with 3D visualization tools (Grafana, Unity, Unreal Engine via AWS integrations), real-time sensor data, and historical analytics.
• Design multi-layer digital twin models — asset twins, process twins, system twins, and enterprise twins — aligned with client operational and strategic goals.
• Drive Digital Twin ROI realization through predictive maintenance use cases, operational simulation, energy optimization, and capacity planning.
• Build reusable Digital Twin accelerators and blueprints that reduce time-to-value for client engagements.

Digital Roadmap Creation & Strategic Advisory

• Lead the creation of advanced, multi-horizon digital transformation roadmaps for enterprise clients, covering:
• Automation Roadmaps — RPA, intelligent automation, AI-augmented workflows, hyperautomation on AWS
• Data Strategy Roadmaps — data platform maturity, governance, monetization, and AI-readiness
• Security Roadmaps — zero-trust architecture, data sovereignty, compliance automation (SOC2, GDPR, HIPAA, PCI-DSS) on AWS.
• AI/GenAI Adoption Roadmaps — use case prioritization, POC-to-production pathways, CoE establishment
• Conduct maturity assessments (data maturity, AI readiness, digital IQ) and translate findings into actionable, business-outcome-aligned roadmaps with prioritized initiatives, investment forecasts, and ROI projections.
• Facilitate executive alignment workshops, architecture review boards, and digital strategy offsites wit CXO stakeholders.

ROI Realization & Value Engineering

• Build and own business case frameworks for AI/ML and analytics investments — quantifying productivity gains, cost avoidance, revenue uplift, and risk reduction.
• Lead POC-to-scale journeys with clear gate criteria, success metrics, and value confirmation at each stage.
• Develop ROI realization dashboards and client-facing value tracking mechanisms post-deployment.
• Present quarterly business reviews (QBRs) to senior client stakeholders highlighting value delivered vs. committed.

Client Advisory & CXO Engagement

• Serve as the trusted AI & Data advisor to CDOs, CDAOs, CTOs, and CIOs of Fortune 500 and large enterprise clients.
• Lead thought leadership engagements — white papers, point-of-view documents, speaking at industry events.
• Manage senior client relationships, navigate complex stakeholder dynamics, and ensure client satisfaction and account growth.

Team Leadership & Capability Building

• Build, lead, and inspire a team of AI/ML engineers, data architects, data scientists, and analytics consultants.
• Establish and lead an internal AI & GenAI Community of Practice (CoP) to foster innovation, knowledge sharing, and accelerator development.
• Drive a culture of responsible, ethical AI within the team and across client engagements.
• Champion upskilling and certification pathways for team members across AWS AI/ML and data services.

Pre-Sales & Business Development

• Own the technical solutioning and estimation for AI/ML, GenAI, and analytics pursuits from discovery to proposal defense.
• Co-develop go-to-market offerings with AWS (Bedrock enterprise offers, SageMaker accelerators, AWS Data & Analytics competency solutions).
• Contribute to revenue targets, account expansion, and new logo acquisition within the AI & Data practice.
• Build relationships with AWS service teams (AI/ML, Analytics, IoT PDMs/PSAs) to access early feature access, co-sell opportunities, and co-innovation programs.

Mandatory skill sets:

Experience

• 15+ years of overall technology experience with a minimum of 10+ years in AWS cloud-based AI/ML, analytics, and data architecture.
• Hands-on delivery experience in production AI/ML, GenAI, and analytics projects with documented ROI realization — not just advisory or oversight roles.
• Proven track record leading large, complex digital transformation engagements in a Big 4, global SI, or top-tier product/consulting company.

• Demonstrable experience delivering projects across at least 4–5 of the following domains:
• Domain
• Enterprise AI/ML platforms on AWS
• Generative AI & LLM applications
• Agentic AI systems & orchestration
• IoT & Industrial IoT (IIoT)
• Digital Twins (AWS IoT TwinMaker)
• Advanced data lakehouse architecture
• Real-time streaming analytics
• Multi-source data ingestion pipelines
• Digital transformation roadmapping
• FinOps for AI/data workloads
• Responsible AI & governance frameworks
• Data mesh / data fabric design

Years of experience Required: 15+ years

Education Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.