Software Architect - AI

RESPONSIBILITIES:Architecture & Technical DirectionDefine and own the end-to-end product architecture, covering backend, AI pipelines, RAG systems, security, and DevOps layers.Ensure scalability, performance, resilience, and security compliance across all platform components.Collaborate with Product and Tech Leads to convert business requirements into architectural blueprints, module designs, and technical specifications.Provide hands-on architectural guidance on GenAI, agent frameworks, retrieval systems, and cloud-native backend services.Drive AI-first architecture decisions, optimizing LLM integration, prompt workflows, LangGraph agents, and vector-based retrieval pipelines.Engineering LeadershipConduct design and code reviews to enforce engineering standards and best practices across all services.Mentor engineering and AI teams on architecture, design patterns, event-driven flows, and cloud-native structures.Work closely with Senior GenAI Engineers to define integration patterns for LLMs, LangGraph agents, and RAG pipelines.Cloud, Infrastructure & DevOpsArchitect and refine infrastructure using AWS CDK (TypeScript) with strong ownership of modular IaC design.Oversee deployments across ECS, Step Functions, Lambda, API Gateway, S3, DynamoDB, SQS, and OpenSearch.Ensure CI/CD automation, environment consistency, and deployment reliability for multi-tenant environments.Drive observability across the platform: CloudWatch dashboards, tracing, logging, and alerting.AI & Data Systems ArchitectureLead the design, deployment, and optimization of LLM-based and Generative AI systems, including prompt engineering, fine-tuning, evaluation, and versioning.Oversee RAG and hybrid retrieval architectures using OpenSearch, embeddings, S3 content indexing, and vector pipelines.Ensure AI pipelines follow robust principles for performance, reproducibility, and continuous validation, including drift detection and monitoring dashboards.Co-lead AI research and experimentation to integrate new model capabilities, enhance automation workflows, and expand the platform’s AI feature set.Define standards for LangGraph and Bedrock/OpenAI model integrations, experiment tracking, and AI module observability.Security, Compliance & ReadinessOversee platform readiness for SOC2, including access control, auditability, logging, data lifecycle, and infrastructure hardening.Drive architectural reviews for API security, network isolation, zero-trust patterns, and secret management.Pre-sales & Technical EnablementSupport pre-sales with solution designs, effort estimations, architecture diagrams, and infrastructure recommendations.Participate in technical discussions with clients evaluating modernization, automation, and enterprise AI capabilities.REQUIREMENTS:Expert-level understanding of cloud-native architecture, microservices, and event-driven systems.Deep hands-on experience in AWS (ECS, Lambda, Step Functions, S3, DynamoDB, OpenSearch, API Gateway, SQS).Strong proficiency in TypeScript and Python, especially with backend, distributed systems, and AI service integration.Proven experience designing scalable GenAI architectures, RAG systems, and LLM-based application patterns.Solid knowledge of containerization, orchestration, IAM, VPC networking, and serverless design.Strong experience with AWS CDK and Infrastructure-as-Code best practices.Good understanding of CI/CD tooling, release strategies, GitOps workflows, and observability stacks.Strong architectural communication, documentation, and diagramming skills (C4, sequence diagrams, component diagrams).QUALIFICATIONS:Bachelor’s or Master’s in Computer Science, Software Engineering, or related disciplines.8+ years in software engineering including 3+ years in architecture or lead engineering roles.Prior experience architecting AI-heavy or cloud-native SaaS platforms is a significant advantage.Proven track record of leading AI teams, deploying LLMs in production, and designing RAG/Generative AI workflows.