Technical Architect(AWS/GCP)

Job Details:

Position Title      :              Technical Architect 

Experience          :              10+ Years

Location               :                Remote

Shift                        :               1:30PM- 11:30PM (UK Shift) 

About the Role

Technical Architect 

Experience:
10+ years of software engineering experience, including 8+ years in solution/enterprise architecture roles and 5+ years designing and operating production-grade cloud-native platforms on AWS and/or GCP. Proven experience leading architecture decisions for large-scale SaaS and AI-driven products.

Role Overview

We are seeking an experienced Technical Architect to define and lead the architecture of scalable, secure, and AI-enabled cloud platforms. The ideal candidate will possess deep expertise in distributed systems, multi-tenant SaaS architectures, cloud-native services, event-driven platforms, and production deployment of Generative AI solutions.

The architect will collaborate with engineering, product, security, DevOps, and data science teams to drive technology strategy, establish architectural standards, and ensure delivery of resilient, cost-efficient, and compliant solutions.

Key Responsibilities

Architecture & Solution Design

• Define end-to-end architecture for cloud-native SaaS applications and AI-powered platforms.

• Design highly scalable, resilient, and fault-tolerant distributed systems.

• Establish architecture standards, design patterns, and technology roadmaps.

• Conduct architecture reviews, technical risk assessments, and solution governance.

• Drive modernization initiatives including cloud migrations and platform transformations.

• Lead technical decision-making across microservices, APIs, databases, AI services, and integration layers.

AI & Generative AI Architecture

• Design and deploy production-grade LLM, RAG, and Agentic AI solutions.

• Define strategies for prompt engineering, context management, chunking, retrieval optimization, and embedding selection.

• Architect vector database implementations and semantic search capabilities.

• Design model evaluation, observability, hallucination detection, and guardrail frameworks.

• Optimize AI workloads for performance, accuracy, scalability, and cost.

• Collaborate with data science and ML teams to operationalize AI pipelines.

Platform & Cloud Engineering

• Architect serverless, containerized, and Kubernetes-based platforms.

• Design CI/CD, Infrastructure-as-Code, security automation, and cloud governance frameworks.

• Establish monitoring, logging, tracing, and operational excellence practices.

• Ensure high availability, disaster recovery, backups, and business continuity standards.

Must-Have Skills

Distributed Systems & Microservices

• Strong expertise in microservices architecture, domain-driven design (DDD), and event-driven systems.

• Hands-on experience with: 

  • Apache Kafka

  • Google Pub/Sub

  • AWS SNS/SQS

  • Amazon Kinesis

• Experience designing asynchronous workflows, event sourcing, and CQRS patterns.

• Strong understanding of API design, service mesh, and integration architecture.

Multi-Tenant SaaS Architecture

• Designing enterprise SaaS platforms supporting multiple clients and business units.

• Tenant isolation strategies (logical, physical, hybrid).

• Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and fine-grained authorization.

• Data residency and compliance-aware architecture.

• Usage metering, billing integration, feature flag management, and tenant onboarding automation.

GenAI & RAG Systems

• Experience building production-ready RAG pipelines.

• Knowledge of: 

  • Prompt engineering and prompt lifecycle management

  • Vector databases and similarity search

  • Embedding generation and optimization

  • Retrieval strategies and ranking mechanisms

  • AI model evaluation frameworks

  • Knowledge-grounded response generation

• Familiarity with AI governance, safety controls, and responsible AI practices.

Security & Compliance

• Data security architecture for enterprise applications.

• PII detection and masking strategies.

• Encryption at rest and in transit.

• Secrets management, key rotation, and identity management.

• Experience with: 

  • SOC 2

  • GDPR

  • ISO 27001

  • Enterprise security reviews and audits

• Zero Trust security principles and least-privilege design.

Performance, Scalability & Cost Optimization

• Experience evaluating trade-offs between: 

  • Cost vs. latency

  • Accuracy vs. scalability

  • Throughput vs. reliability

• Designing cost-efficient AI and cloud workloads.

• Capacity planning and performance optimization.

• FinOps best practices and cloud cost governance.

Cloud Technology Expertise

AWS

Strong hands-on experience with:

• Amazon Bedrock

• Amazon SageMaker

• AWS Lambda

• ECS / EKS

• API Gateway

• Amazon S3

• Amazon DynamoDB

• Amazon OpenSearch

• Amazon Transcribe

• Amazon Comprehend

• AWS Step Functions

• CloudWatch

• IAM

• AWS KMS

• CloudFormation / Terraform

GCP

Strong hands-on experience with:

• Vertex AI

• Google Kubernetes Engine (GKE)

• Cloud Run

• Cloud Functions

• Cloud Storage

• BigQuery

• Pub/Sub

• Speech-to-Text

• DLP API

• Cloud Monitoring

• Cloud Logging

• IAM

• Cloud KMS

• Terraform

Leadership & Collaboration

• Lead architecture discussions with senior stakeholders and clients.

• Mentor engineering teams on architectural best practices.

• Drive technical design reviews and solution governance.

• Translate business requirements into scalable and maintainable technical solutions.

• Collaborate across engineering, product, data science, security, and operations teams.

Nice-to-Have

• Multi-cloud architecture and migration experience (AWS ↔ GCP).

• Contact center, customer experience, or conversational analytics domain knowledge.

• Experience with transcript analytics, sentiment analysis, QA automation, or knowledge management platforms.

• Exposure to MLOps, LLMOps, and AI observability platforms.

• Experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or OpenSearch Vector Engine.

• Knowledge of agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.

• Experience building enterprise AI products with governance and compliance requirements.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.

• AWS Solution Architect Professional, AWS Machine Learning Specialty, Google Professional Cloud Architect, or equivalent certifications.

• Demonstrated experience architecting enterprise-scale AI and SaaS platforms serving large customer bases.