Director of Innovation Delivery

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Location not statedSeniorPublished 2 February 2026Ghost risk: high

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First recorded by Psst: 13 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.

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The 20-second read

Experience
Senior
Where you can live
Location not stated
Skills and tools
python, typescript, terraform
Job type
Full-time

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Job details

Where you can work
Location not stated
Employment type
Full-time
Advertised pay
Not stated by the employer
Experience
Senior
Employer publication date
2 February 2026
First recorded by Psst
13 October 2026
Last checked at the source
9 November 2026

About the job

Job Summary

As a Director of Innovation Delivery 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.

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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