# tribe.ai — Forward Deployed AI Architect

- Generated: 2026-09-15 10:48:11 PM EDT
- Original/canonical posting: https://wellfound.com/jobs/4532096-forward-deployed-ai-architect
- Provider: Wellfound
- Posted: 2026-07-31T04:32:01Z
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp when available
- Applicants: Not disclosed
- Work model/location: Remote — United States
- Compensation: Not disclosed; Architect title does not meet Keith's undisclosed-compensation exception
- Travel: Not disclosed; forward-deployed consulting role
- Positioning track: Technical IC
- Fit outcome: FAIL — 90%

## Direct-match strengths

Production AI architecture, Python, LLMs, RAG, agents, evaluation, vectors, cloud systems, enterprise discovery, executive communication, reusable frameworks, and hands-on delivery.

## Hard or material gaps

Hard policy conflicts: compensation is undisclosed for a non-Director/VP/Chief title, and the employer explicitly describes rotating engagements that include defense, which Keith excludes. The technical fit is otherwise excellent.

## Evidence map

1. Design production LLM, RAG, agent, and evaluation systems (weight 3, evidence 3/3) — Direct architecture-through-operation evidence.
2. Hands-on Python and distributed cloud systems (weight 3, evidence 3/3) — Direct Python, AWS, APIs, data, and production platform evidence.
3. Enterprise technical discovery (weight 3, evidence 3/3) — Advised 200+ enterprises and translated ambiguous needs into architecture and roadmaps.
4. Lead technical teams while remaining an IC (weight 3, evidence 3/3) — Direct player-coach and hands-on founder evidence.
5. Reusable frameworks and practices (weight 2, evidence 3/3) — Built accelerators, standards, evaluation, and governance patterns.
6. Defense-free scope (weight 3, evidence 0/3) — Posting explicitly includes defense engagements.
7. Eligible compensation evidence (weight 3, evidence 0/3) — Compensation is undisclosed for an Architect title.

## Keyword diagnostic

Exceptional forward-deployed AI architecture match, rejected by undisclosed compensation and explicit defense-engagement exposure.

## Full normalized job description

About Tribe AI
At Tribe, we're helping the world's largest companies turn AI into a competitive advantage. Every enterprise wants AI. Very few know how to build systems that actually survive production.
That's where we come in.
We work alongside companies ranging from Fortune 500s to ambitious startups, designing and delivering production AI systems that solve real business problems—not demos. Our teams partner directly with OpenAI, Anthropic, and the broader frontier AI ecosystem, giving us early access to emerging capabilities while staying relentlessly focused on one thing:
Shipping AI that works.
About the Role
We're looking for a Forward Deployed AI Architect who can walk into an enterprise, understand a messy business problem, and leave behind a production system people actually depend on.
This isn't a PowerPoint architecture role.
You'll spend your time talking to executives in the morning, reviewing agent orchestration with engineers after lunch, debugging production issues in the afternoon, and redesigning an AI workflow before dinner. You'll own technical direction while staying hands-on enough to earn the trust of every engineer in the room.
The best architects we've met are still exceptional builders.
About what you'll Do
Design production AI systems
Architect end-to-end AI applications using LLMs, RAG, agents, structured workflows, evaluation pipelines, and modern cloud infrastructure.
Make pragmatic technical decisions around latency, reliability, observability, governance, and cost.
Design systems that continue working after the demo.
Work directly with enterprise customers
Lead technical discovery sessions.
Translate vague business problems into concrete engineering plans.
Build trust with everyone—from staff engineers to CTOs.
Stay hands-on
Prototype difficult pieces yourself.
Unblock engineering teams when projects get complicated.
Review architecture through implementation—not just diagrams.
Raise the bar
Turn project lessons into reusable frameworks.
Improve internal best practices.
Help shape how modern enterprise AI gets built.
What We're Looking For
You probably have:
8+ years building production software.
Deep experience shipping AI products into production.
Strong Python engineering skills.
Experience with modern AI frameworks, including agent systems, RAG, orchestration frameworks, vector databases, evaluation pipelines, and LLM APIs.
Experience designing distributed cloud systems on AWS, Azure, or GCP.
Strong systems thinking—you understand infrastructure as well as models.
Excellent communication skills with technical and executive audiences.
Bonus points if you've:
Worked as a consultant or forward-deployed engineer.
Built internal AI platforms.
Founded a startup.
Led technical teams while remaining an individual contributor.
Built AI systems in regulated environments like healthcare, finance, cybersecurity, or government.
The Kind of Person Who Thrives Here
You're someone who:
Ships instead of theorizes.
Enjoys ambiguity more than requirements documents.
Learns new models faster than they're released.
Doesn't panic when production breaks.
Thinks in tradeoffs—not absolutes.
Can explain complex AI systems without sounding complicated.
Cares more about customer outcomes than technical elegance.
You don't need to know every framework. You need to know how to figure things out.
About Tribe
Real Problems:
Build AI systems that become part of enterprise operations—not innovation theater.
Exceptional People:
Work alongside engineers, researchers, founders, and operators who've built products at companies like OpenAI, Meta, Google, Amazon, Microsoft, and dozens of successful startups.
Constant Variety:
Every engagement is different. Healthcare one month. Finance the next. Defense after that.
Frontier AI:
Stay close to the newest models through our partnerships with OpenAI and Anthropic.
Career Growth:
You'll become a stronger architect, engineer, consultant, and technical leader—all at the same time.
This role is ideal for engineers who've already built AI systems in production and now want to solve harder problems across multiple industries. If you've founded a company, led technical teams, consulted with enterprise customers, or simply enjoy turning ambiguity into working software, we'd love to talk.

## Artifact metadata

- Resume: Not generated because the fit gate returned FAIL.
- Cover letter: Not generated because the fit gate returned FAIL.
- LinkedIn note: Not generated for a FAIL role.
- Google Drive used: No