Senior AWS Application Architect

Job Description

About Company

HCLSoftware, founded in 2019, is the software business division of HCLTech. We develop, market, and sell software products across various categories, including Business & Industry Applications, Cybersecurity, Data & Analytics, AI & Intelligent Operations, Sovereign Collaboration, Total Experience, and Specialized Software.

We drive customer success through continuous product innovation, serving over 20,000 organizations, including many Fortune 100 and Fortune 500 companies. We are also a proud partner of Scuderia Ferrari.

As a fast-growing, $2B+ software business, we have an incredible global workforce of 8,000+ employees. Join us and make an impact from Day 1—this is an exciting time to be part of HCLSoftware as we expand, invest, and grow!

We are seeking a passionate, hands-on and experienced Senior AWS Application Architect for the products under HCLSW AI and Intelligent Operations division. The individual will be working under Central Engineering team and will be responsible for design, build, and evolving HCLSW cloud application platform and customer‑facing products on AWS applying the AWS Well‑Architected Framework to deliver secure, reliable, high‑performing, and cost‑efficient applications and platforms, while enabling teams through self‑service paved roads, guardrails, and automation.

Location- Noida/Bangalore

Responsibilities:

Product & Platform Architecture (Hands‑on)

Lead architecture and contribute code/blueprints for containerized microservices on App Runner/Amazon EKS/ECS, AWS Fargate, and Amazon ECR (image promotion, vulnerability scanning, lifecycle & replication).

Define global performance patterns using AWS Global Accelerator for low‑latency user experiences; design active/active or fast failover as needed.

Build and maintain a product‑grade internal developer platform: standardized IaC with Ansible/Cloudformation/Terraform, cluster bootstrapping via EKS Blueprints (Ingress/ALB Controller, CI/CD, Prom/Grafana), and Service Catalog portfolios for self‑service.

AI‑Augmented Applications

Design and integrate Generative AI capabilities with Amazon Bedrock (model selection, Guardrails, Agents, Knowledge Bases/RAG, provisioned throughput/inference profiles) into product workflows with appropriate safety and governance.

Establish MLOps on Amazon SageMaker (Pipelines, Model Registry, Monitoring) for batch/real‑time inference and lifecycle management.

Data & Analytics

Architect governed data platforms with AWS Aurora, RDS, AWS Glue, Lake Formation, query via Amazon Athena, and integrate Amazon Redshift where appropriate.

Security, Identity & Product Security

Implement defense‑in‑depth using IAM, IAM Identity Center (SSO), AWS Security inspector, AWS Guard duty, AWS Detective, AWS Organizations with SCP guardrails; centralize visibility via AWS Security Hub.

Protect web APIs and apps with AWS NGFW, WAF managed rules (including Bot Control) and, where needed, AWS Shield for DDoS resilience.

Continuously detect threats with Amazon GuardDuty, routed to AWS Security Hub for triage/automation.

SRE/Operations, Observability & Performance

Demonstrated ability to manage performance engineering for multiple complex products and influence product designs to deliver superior product performance with less cost.

Platform Engineering & Cloud Foundations

Operate a secure multi‑account landing zone with AWS Control Tower and Landing Zone Accelerator (LZA); apply region‑deny and SCP guardrails, central logs, and detective controls.

FinOps & Cost Efficiency

Apply FinOps best practices for cloud cost management and resource optimization. Institute FinOps capabilities (allocation, unit economics, KPI/benchmarking, rightsizing, autoscaling/scale‑to‑zero) and align engineering trade‑offs to value.

Required Qualifications:

• 10+ years overall in software/platform architecture; 5+ years building on AWS at scale with consistent application of the AWS Well‑Architected pillars.
• AWS certifications such as Solutions Architect – Professional, DevOps Engineer – Professional, Security Specialty, Data Analytics or ML Specialty.
• Govern AI using NIST AI RMF and ISO/IEC 23894; awareness of EU AI Act tiers and GPAI duties.
• Strong understanding of enterprise infrastructure/software development and testing processes, in on-premises (compute, storage, networking) or Cloud (SaaS).
• Proven hands‑on experience shipping product features and platform capabilities: Automation using IaC (Ansible/Terraform), CI/CD automation/ Supply‑chain security in CI/CD /add‑on blueprints,
• GenAI and ML delivery using Amazon Bedrock (Guardrails/Agents/Knowledge Bases) and SageMaker (Pipelines/Model Registry/Monitor).
• Identifies misalignments with goals, objectives, and work direction against the organizational strategy. Makes suggestions for the course correct.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork skills.
• Expertise in Zero Trust architecture patterns for services and data access.
• Awareness of industry frameworks, security compliance and regulations like NIST Cybersecurity Framework 2.0, NIST SP 800‑53 Rev.5, GDPR (EU), TOGAF Standard.