Salary
≈ $53k – $121k per year (Estimated)
Location
Remote (Pakistan)
Seniority
Architect
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Feb 23, 2026. Creative Chaos scores D on the Alion truth index.
Overview
Company
Impact
Profile match
Creative Chaos is a software development and technology services firm that builds custom applications and mobile products and now sells AI automation projects to startups and enterprises, with its headquarters listed in San Francisco and Boston. Operating since 2000 with a global delivery network of more than 300 full-time staff, it reports long-running engagements with clients such as McDonald's, Coca-Cola, Foxtons and Qlik. Its openings are mostly for senior and principal software engineers in React, Node, Python, Java, .NET, Ruby on Rails and Vue, along with DevOps engineers, iOS and Unity developers and technical delivery managers.
Job Summary:
As an AI Architect you will build AI-native products. You’ll lead cross-functional Innovation Delivery Squads-owning outcomes end-to-end across web, mobile, AI agents, and streaming backends. You’re 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
- 8-12+ 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).
Tech stack (you have hands on experience)
- 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: Next.js 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.
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