Founding AI Engineer (LLMs & Agents)

Reposted Yesterday
Be an Early Applicant
2 Locations
Hybrid
180K-260K Annually
Expert/Leader
Artificial Intelligence • Machine Learning • Business Intelligence • Financial Services • Big Data Analytics • Manufacturing
Skiffra is building the intelligence layer for the physical world.
The Role
The Founding AI Engineer will design and implement production-grade AI systems focused on orchestrating complex workflows using LLMs and modern AI tools. Responsibilities include architecting, building, and optimizing systems while collaborating with founders and partners on product development.
Summary Generated by Built In
About Skiffra

Skiffra is building the intelligence layer for the physical world. We translate complex, real-world environments into clear, actionable data.
While most AI companies focus on digital industries, we design AI native orchestration systems for the sectors that extract, move, and build ecosystems around us. We turn messy, high stakes operations into intelligent, adaptive workflows that improve decisions in real time.
Our first proving ground is mining and natural resources, but the platform is modular by design and built to scale into any industry where decisions are expensive and the consequences are real.

The Role

As a Founding AI Engineer, you will be the architect of our core intelligence. This is a role for a high-leverage builder who can move fluidly between prompt engineering, backend systems, and model optimization. You will design the "brain" of Skiffra, moving agentic workflows from whiteboards to production-grade systems that handle real enterprise data at scale. This is a founding-level role for builders who value shipping over dogma and real-world impact over demos.

This role will be based in the San Francisco Bay Area or Los Angeles, CA.

What You’ll Do
  • Architect & Build Agentic Systems: Design, prototype, and harden production-grade orchestration frameworks that leverage LLMs, persistent memory, and tool-integration to navigate complex, non-linear enterprise tasks

  • Build the Data Flywheel: Implement sophisticated RAG (Retrieval-Augmented Generation) pipelines, ensuring high-fidelity context retrieval from fragmented data sources

  • Evaluate & Iterate: Build internal benchmarking and evaluation suites to measure and improve model reliability, grounding, and latency

  • Strategic Modeling: Architect high-performance intelligence stacks by making pragmatic trade-offs between Frontier Reasoning Models (GPT-5, Claude 4 Opus) for long-horizon agentic planning, Fine-tuned Open-Weight Models (Llama 4, Mistral 3) for data sovereignty and low-latency inference, and Deterministic Heuristics for reliable, cost-efficient guardrails

  • Full-Stack Ownership: Work directly with founders to translate ambiguous operational "messes" into clean, scalable, AI-powered software

  • Cross-Collaboration: Partner with product and engineering to turn ambiguity into working software

What We’re Looking For
  • 7+ years of Systems Engineering: You have a deep background in building production software. You understand that "AI" is only as good as the infrastructure surrounding it

  • Modern AI Fluency: Deep practical experience with the transformer-based stack: embeddings, vector databases, tool-calling, and context window management

  • Python Power-User: You are comfortable building entire systems, not just experimenting in notebooks

  • Reliability Mindset: You have strong instincts for failure modes (hallucinations, API timeouts, "infinite loops" in agents) and how to build guardrails against them

  • Clear communicator with founder-level ownership mindset

Nice to Have
  • Experience in building complex, multi-step workflows using LangGraph, LlamaIndex, and CrewAI

  • Hands-on experience with Fine-tuning and PEFT (LoRA/QLoRA) to adapt open-weight models for domain-specific tasks

  • A background in Enterprise Operations (Industrial, Logistics, Fintech, or CRM workflows).

  • Strong opinions on where AI creates value and where it’s just expensive noise

How We Work

We value speed, clarity, and technical rigor. We favor simple systems over clever ones, prototypes over over-planning, and ownership over handoffs. You’ll work directly with founders and ship things that matter quickly.

Location & Work Model

This is a hybrid role with regular in-person collaboration in Los Angeles or the San Francisco Bay Area. We are not a remote-only company.

Work Authorization

Candidates must be authorized to work in the United States. We are not able to offer visa sponsorship for this role.

Benefits & Eligibility

This position is eligible for Skiffra’s standard benefits, including health insurance and retirement plans, and may also qualify for participation in the Company’s bonus and incentive programs.

Equal Opportunity

Skiffra is an equal opportunity employer. We value diversity and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic.

Top Skills

Fine-Tuning
Llms
Peft (Lora/Qlora)
Python
Rag (Retrieval-Augmented Generation)
Tool-Integration
Transformer-Based Stack
Vector Databases
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The Company
3 Employees
Year Founded: 2025

What We Do

We translate complex, real-world environments into clear, actionable data. While most AI companies focus on digital industries, we design AI native orchestration systems for the sectors that extract, move, and build ecosystems around us. We turn messy, high stakes operations into intelligent, adaptive workflows that improve decisions in real time. Skiffra is led by Co-founders George Whitehouse, former head of Digital Transformation at Toyota who rebuilt complex mining operations into integrated, data driven systems, and Andy Smith, Intel and Dolby operator turned GP and 0-to-1 startup builder with more than 40 companies founded, advised, or invested and exits to DigitalOcean, IBM, Assa Abloy, and Cisco. In one recent nine month proof of concept focused on four value centers, the Skiffra team turned a 5 million dollar investment into a sustained 100 million dollar EBITDA lift for the client. Together they combine deep industrial execution with venture scale product discipline to build an AI operating system for mining first, and the wider physical world next.

Why Work With Us

We are well funded, offer best in class benefits and are building our founding technical team to work alongside our co-founders. Our first proving ground is mining and natural resources, but the platform is modular by design and built to scale into any industry where decisions are expensive and the consequences are real.

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