Solution Architect

Job Description

We are seeking an experienced Technical Lead / Solution Architect to design anddeliver enterprise-grade, multi-cloud and AI-enabled solutions. The role will provide technical leadership across application, data, integration, security, cloud, and observability, with a strong focus on Generative AI, Agentic AI,RAG, and LLMOps. The successful candidate will lead client engagements, architecture design,proof of concepts, and technical delivery across AWS, Azure, and GCPenvironments.

Key Responsibilities

• Translate business requirements into scalable GenAI and Agentic AI solution architectures, including RAG and AI agent-based solutions.
• Own end-to-end architecture across applications, data, integrations, security, infrastructure, and observability.
• Provide technical leadership for client opportunities, solution discussions, and implementation engagements.
• Lead the design and development of POCs and MVPs, guiding engineeringteams through build, deployment, and operationalization.
• Establish and implement LLMOps practices, including model evaluation, tracing, observability, guardrails, prompt management, versioning, and quality metrics.
• Design batch and streaming data architectures, vector search capabilities,APIs, events, and agent/tool integration contracts.
• Evaluate and recommend appropriate cloud platforms, AI models, managedservices, and open-source technologies based on cost, performance, scalability,and security.
• Design secure solutions using Zero Trust, IAM, OAuth2/OIDC, secrets management,KMS, data classification, and access controls.
• Define APIs and integration architectures using REST, gRPC, GraphQL, andevent-driven patterns.
• Lead architecture reviews, design reviews, code reviews, and technicalgovernance activities.
• Plan technical roadmaps, delivery backlogs, estimates, dependencies, and implementation strategies across multidisciplinary teams.
• Work closely with clients and stakeholders to communicate technical decisions, risks, benefits, cost considerations, and ROI.
• Coach and mentor engineering teams and establish reusable architecture patterns, templates, and reference implementations.
• Manage multiple client opportunities and technical initiatives while maintaining strong stakeholder relationships.

Technical Requirements

• Strong hands-on experience across AWS, Azure, and GCP.
• Minimum 3 years of hands-on experience in each of AWS, Azure, and GCPenvironments.
• At least 1 year of hands-on experience with Generative AI and Agentic AItechnologies.
• Experience designing and delivering production-grade RAG and AI agentsolutions.
• Hands-on experience with at least one AI/agent framework, such as:
• LangChain / LangGraph DSPy OpenAI or Anthropic tool use Databricks Agents Equivalent AI agent frameworks
• Strong experience with LLMOps, including:
• AI model and application evaluation
• LLM judges and task-based metrics
• MLflow / OpenTelemetry tracing and observability
• Prompt and version management
• CI/CD for AI applications
• AI safety and guardrails
• Strong data platform experience with Delta Lake, Apache Iceberg, or ApacheHudi .
• Experience with streaming technologies such as Kafka, Kinesis, or GooglePub/Sub.
• Hands-on experience with vector databases/search technologies such as Databricks Vector Search, pgvector, Pinecone, Milvus, or Vespa.
• Experience with Kubernetes, containers, serverless architectures, andInfrastructure as Code using Terraform and/or CloudFormation.
• Strong understanding of microservices, distributed systems, API design, andevent-driven architecture.
• Good understanding of web and mobile application architectures.

Qualifications & Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering,Data Science, or a related discipline.
• 12+ years of experience in enterprise application, cloud, dataplatform, or solution architecture .
• Minimum 2 years of experience designing and delivering production-grade GenerativeAI solutions.
• Strong exposure to Data Science and Machine Learning.
• Proven experience leading architecture and technical delivery acrosscomplex enterprise environments.
• Strong client-facing, stakeholder management, communication, and influencingskills.
• Ability to manage multiple technical opportunities and competing priorities.
• Strong analytical and problem-solving skills with the ability to translatecomplex technical concepts into clear business outcomes.

Required Certifications

Candidates should hold relevant certifications across the following areas:

• AWS, Microsoft Azure, or Google Cloud AI Certifications
• AWS, Microsoft Azure, or Google Cloud Data Science / Machine LearningCertifications
• AWS, Microsoft Azure, or Google Cloud Solution Architect Certifications
• TOGAF 9 Certification
• Other equivalent industry-recognised architecture certifications are anadvantage.