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This role owns the software and cloud-native architecture of AI-enabled applications and retrieval systems, from design to production. It combines architectural leadership with hands-on engineering: designing GenAI and RAG solutions, building cloud-native backend services, and ensuring the security, reliability, and observability required for production workloads. Requirements What you will do Design scalable, secure, and resilient architectures for AI-enabled applications, defining service boundaries, data flows, APIs, and integration patterns. Define cloud-native patterns across microservices, containers, serverless, and event-driven systems. Design and productionize GenAI and RAG solutions: model selection and routing, retrieval strategy, evaluation, guardrails, and cost/latency optimization. Build backend services in TypeScript/Node.js and/or Python, and event-driven workflows with queues, workers, and webhooks. Define non-functional requirements, evaluate trade-offs, and document decisions in ADRs. Translate business use cases into technical designs, assessments, and executive summaries. Own the architecture from discovery to go-live, guiding engineers through architecture and code reviews. Implement observability and secure CI/CD pipelines. Job requirements 7+ years of software engineering experience. Proven experience owning the architecture of production distributed systems (microservices, domain-driven design, REST and asynchronous APIs). Hands-on delivery of production GenAI or LLM applications, including evaluation and AI safety controls. Experience with RAG, embeddings, and vector databases (pgvector, OpenSearch, or equivalent). Strong TypeScript/Node.js or Python engineering experience. Deep knowledge of cloud-native patterns: containers and Kubernetes, serverless, event-driven messaging, and resilience patterns. Strong understanding of security in cloud-native systems: identity, authorization, secrets management, and data protection. Docker, CI/CD, automated testing, and observability (OpenTelemetry, Grafana, Datadog, or CloudWatch). Nice to have AWS: Bedrock, Lambda, API Gateway, SQS, EventBridge, Step Functions, ECS/EKS, Aurora PostgreSQL, DynamoDB. Conversational and contact center: WhatsApp Business API, Amazon Connect, Amazon Lex, Twilio, voice bots. Terraform, CloudFormation, or CDK. AWS Certified Solutions Architect – Professional or equivalent. Customer-facing consulting experience and comfort presenting to executive stakeholders. Engagement details Part time Remote Contractor Hourly Start: ASAP Highlights AWS (Bedrock, Lambda, SQS, EventBridge), GenAI / LLM, RAG & Vector Databases (pgvector, OpenSearch), TypeScript / Node.js, Python, Kubernetes, Docker, PostgreSQL, Terraform / CloudFormation / CDK Originally posted on Himalayas