AI Architect Creative Chaos

Karachi - Pakistan

Monthly Salary: Not Disclosed

Posted on: 20 hours ago

Vacancies: 1 Vacancy

Job Summary

Our client Creative Chaos is looking for AI Architect to work remotely.
Job Summary:
As an AI Architect you will build AI-native products. Youll lead cross-functional Innovation Delivery Squadsowning outcomes end-to-end across web mobile AI agents and streaming backends. Youre a hands-on technical leader who can scope architect staff and ship; then run the product safely at scale.

Job Responsibilities:

Stand up and run squads (Discovery Prototype Product Platform & SRE).
Design and ship RAG/agent systems: pick models (e.g. Anthropic Claude OpenAI Google or open-weights like Llama/Mistral) define tools/functions and choose retrieval (default Postgres pgvector scale to Weaviate/Qdrant/Pinecone when needed).
Operate AI safely: evals & guardrails structured outputs (JSON/Schema) PII redaction refusal policies cost/latency budgets and LLM observability.
Own delivery outcomes: SLOs quality cost velocity; release with feature flags and canaries.
Be client-facing: discovery scoping SoW roadmap QBRs.
Hire/coach Tech Leads EMs and PMs; level up practices.

Requirements

812 yrs engineering; 4 yrs leading multi-team delivery; shipped production web/mobile systems at scale.
Shipped at least one production AI app using Claude/GPT/Gemini/Llama/Mistral backed by retrieval (pgvector or a vector DB) and a basic eval/guardrail pipeline.
Implemented orchestration (LangGraph/DSPy or Temporal for durable workflows) rerankers (e.g. Cohere/Jina/Voyage) and prompt/tool versioning.
Built with modern cloud data: serverless/K8s Terraform OpenTelemetry feature flags/experimentation.
Excellent client communication and commercial sense (SoWs staffing utilization).
Models: Anthropic Claude; OpenAI; Google; open-weights (Llama Mistral).
Orchestration & agents: LangGraph (or DSPy) for graphs; Temporal for durable long-running tasks and SLAs.
Retrieval: Postgres pgvector (default); Weaviate/Qdrant/Pinecone when scale/ops require; hybrid search with OpenSearch/Typesense.
Embeddings / rerankers: OpenAI/Voyage/E5/BGE; Cohere/Jina/Voyage rerank.
Guardrails & evals: JSON/Pydantic schemas red-team sets promptfoo/Ragas/DeepEval; content/PII filters.
Observability: OpenTelemetry traces incl. prompt/tool spans; Langfuse/Arize Phoenix (or equivalent) Sentry/Grafana.
App & data: 15 (RSC) TypeScript/Go/Python; Postgres; Kafka/Redpanda/NATS; dbt/lakehouse optional.
Ops: Cloud Run/ECS/K8s; Terraform/OpenTofu; GitHub Actions; LaunchDarkly/Unleash; Statsig/GrowthBook.

Our client Creative Chaos is looking for AI Architect to work remotely.Job Summary:As an AI Architect you will build AI-native products. Youll lead cross-functional Innovation Delivery Squadsowning outcomes end-to-end across web mobile AI agents and streaming backends. Youre a hands-on technical lea...

Job Responsibilities:

Stand up and run squads (Discovery Prototype Product Platform & SRE).
Design and ship RAG/agent systems: pick models (e.g. Anthropic Claude OpenAI Google or open-weights like Llama/Mistral) define tools/functions and choose retrieval (default Postgres pgvector scale to Weaviate/Qdrant/Pinecone when needed).
Operate AI safely: evals & guardrails structured outputs (JSON/Schema) PII redaction refusal policies cost/latency budgets and LLM observability.
Own delivery outcomes: SLOs quality cost velocity; release with feature flags and canaries.
Be client-facing: discovery scoping SoW roadmap QBRs.
Hire/coach Tech Leads EMs and PMs; level up practices.

Requirements

812 yrs engineering; 4 yrs leading multi-team delivery; shipped production web/mobile systems at scale.
Shipped at least one production AI app using Claude/GPT/Gemini/Llama/Mistral backed by retrieval (pgvector or a vector DB) and a basic eval/guardrail pipeline.
Implemented orchestration (LangGraph/DSPy or Temporal for durable workflows) rerankers (e.g. Cohere/Jina/Voyage) and prompt/tool versioning.
Built with modern cloud data: serverless/K8s Terraform OpenTelemetry feature flags/experimentation.
Excellent client communication and commercial sense (SoWs staffing utilization).
Models: Anthropic Claude; OpenAI; Google; open-weights (Llama Mistral).
Orchestration & agents: LangGraph (or DSPy) for graphs; Temporal for durable long-running tasks and SLAs.
Retrieval: Postgres pgvector (default); Weaviate/Qdrant/Pinecone when scale/ops require; hybrid search with OpenSearch/Typesense.
Embeddings / rerankers: OpenAI/Voyage/E5/BGE; Cohere/Jina/Voyage rerank.
Guardrails & evals: JSON/Pydantic schemas red-team sets promptfoo/Ragas/DeepEval; content/PII filters.
Observability: OpenTelemetry traces incl. prompt/tool spans; Langfuse/Arize Phoenix (or equivalent) Sentry/Grafana.
App & data: 15 (RSC) TypeScript/Go/Python; Postgres; Kafka/Redpanda/NATS; dbt/lakehouse optional.
Ops: Cloud Run/ECS/K8s; Terraform/OpenTofu; GitHub Actions; LaunchDarkly/Unleash; Statsig/GrowthBook.