Key Facts

Remote From:

Pakistan

Full time

Expert & Leadership (>10 years)

English

Hard Skills

Other Skills

•
Team Leadership

Roles & Responsibilities

8-12+ years engineering experience
4+ years leading multi-team delivery and shipping production web/mobile systems at scale
Proven track record shipping at least one production AI app (Claude, GPT, Gemini, Llama, or Mistral) with retrieval (pgvector or a vector DB) and a basic eval/guardrail pipeline
Experience with orchestration and durable workflows (LangGraph/DSPy or Temporal), rerankers (Cohere/Jina/Voyage), and prompt/tool versioning

Requirements:

Stand up and run cross-functional squads (Discovery, Prototype, Product, Platform, SRE) and own end-to-end delivery outcomes
Design and ship RAG/agent systems: select models, define tools/functions, and choose retrieval strategies
Operate AI safely: evals, guardrails, PII redaction, refusal policies, cost/latency budgets, and observability
Be client-facing: discovery, scoping, SoWs, roadmap, QBRs; hire/coach Tech Leads, EMs, and PMs

Job description

Our client Creative Chaos is looking for AI Architect to work remotely.
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).
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.