Forward Deployed Engineer
Posted 2 days ago
The role in short
Embed with clients to design, build, and deploy end-to-end production AI solutions including LLM integrations, RAG pipelines, and agentic workflows.
About Zetta2 (ZettaSquared)
At Zetta², we’re on a mission to help enterprises realize the value of AI for their business. We’re a pure-play, agnostic AI-native firm that provides a full range of AI infrastructure and software products, solutions, agentic workflows and services, alongside leading AI technologies and best-in-class partnerships, helping enterprises drive measurable business outcomes, quickly taking AI solutions from idea to production.
ZETTA² integrates leading AI models, hyperscale platforms, and AI technologies to deliver secure, production-ready AI-native solutions. Our vendor-neutral approach enables us to recommend the best technology or ground-up approach for each customer — not just a preferred platform. We continually vet partners from the fast-moving AI world and have strategic partnerships with many of the industry’s leaders. We work with Google, Amazon Web Services, Oracle, IBM, OpenAI, Anthropic, Nvidia, Cursor, Grok by X, Typesafe AI, Thinking Machines, Apache Iceberg, Databrinks, WorkOS, Zapier, Unsloth, Snowflake, Ping Identity, Pinecone, ServiceNow, Microsoft, Salesforce and many more AI stack industry leaders.
ZETTA² raised a substantial seed round in August of 2026, led by Smith/Newberg Road Partners, L.P./Bekman 514, Ltd. Smith, with sales in excess of $12B, is one of the world's largest independent electronic-component distributors, offering supply chain services on a global scale.
About the Role – Forward Deployed Engineer
We're looking for several Forward Deployed AI Engineers to join our team and support our most mission-critical client engagements. You'll be in the field — shoulder-to-shoulder with other ZETTA² engineers and our clients — designing, building, and deploying end-to-end AI solutions.
This is not a demo-building role. Forward Deployed AI Engineers are hands-on builders. They design, implement, deploy, and iterate on end-to-end AI systems in close partnership with customers, subject matter experts, and other ZETTA² engineers.
Key Responsibilities:
Client Engagement
· Work side-by-side with our client’s technology and engineering teams and the ZETTA² consulting team to support full stack AI-native deployments.
· Build and integrate AI solutions systems using open and closed LLMs, RAG pipelines, agentic frameworks and workflows, vector DBs, and related tools.
· Translate high-level designs into working components that deliver measurable outcomes.
· Write modular, reusable code that balances speed of delivery with long-term maintainability.
· Debug relentlessly - optimize for reliability in production, not just elegance in code.
Delivery & Enablement
· Partner with ZETTA² Senior Forward Deployed Engineers/Architects and the leadership team to translate client-specific solutions into reusable proprietary AI products, solutions, agentic workflows, and services.
· Share insights across the company and team, raising the bar for future deployments.
About You
· Experience designing and delivering enterprise AI-native solutions. You have built applications powered by LLMs or other AI models and are comfortable composing multiple components — prompts, agents, tools, retrieval, evaluators, workflows, and integrations — into end-to-end systems.
· 1-2 years software engineering experience, designing and delivering enterprise software systems, with strong AI/ML depth.
· Strong programming experience with Python or TypeScript.
· Exposure to agent frameworks and orchestration tools.
· Experience using AI-assisted development tools such as Codex, Cursor, or Claude Code.
· Ability to engage credibly across technical audiences – from business executives to technologists and engineers.
· Ability to travel - typically 10–50%, depending on the project, customer needs, and your role on the engagement.
· Background in consulting or client-facing engineering roles.
What We Offer
The base salary range for this role is $80K – $150K, total salary for role expected to be $100K – $200K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful early-stage equity, quarterly and year-end bonuses, along with a comprehensive benefits package:
· 100% coverage of medical, dental, and vision insurance for employees and dependents.
· Ongoing training across our strategic AI partners.
· Access to state-of-the-art AI models, generous usage of modern AI tools, and exciting customers with real-world business problems.
· Complementary in-office lunches and snacks provided.
· Ownership of high-impact projects across some of the world’s best companies.
· Flexible time off.
· Relocation assistance.
· Enjoy a fast-moving culture that values the desire and ability to learn AI technologies while having fun.
ZETTA² has offices in Houston, Los Angeles (2027) & Boston (2027).
We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Prep for this interview
5 questions likely to come up at Zetta2, each matched to a line in this posting.
- 1LLMs, RAG and agents
They wrote: “Build and integrate AI solutions systems using open and closed LLMs, RAG pipelines, agentic frameworks and workflows, vector DBs, and related tools.”
A customer wants a chatbot over their internal documents. How do you build it?
How to answer
Why they ask: RAG is the most common first project. They want the whole path, from messy files to answers people trust.
- Collect and clean the documents; handle permissions per user
- Split them into chunks, embed, and store with source links
- Retrieve, then answer with citations; say “I don't know” when retrieval is weak
- Build a test set of real questions with expected answers before launch
Tip: Spend more time on the data and on testing than on the model.
- 2Coding
They wrote: “Strong programming experience with Python or TypeScript.”
Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.
How to answer
Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.
- Read with a proper CSV parser; check the header first
- Validate each row and collect errors, not crash on the first one
- Send in batches with retries and a clear report at the end
- Write one or two quick tests for the parsing
Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.
- 3Discovery and scoping
They wrote: “Access to state-of-the-art AI models, generous usage of modern AI tools, and exciting customers with real-world business problems.”
A customer says “we want AI in our claims process.” What do you ask in the first meeting?
How to answer
Why they ask: Most FDE work starts this vague. They want to hear you find the real problem before you pick a tool.
- Map the current process: who touches a claim, in what order, with which systems
- Find the slowest or most error-prone step and ask what it costs them
- Agree on one measurable goal (for example time per claim, or error rate)
- Ask what data you can access, and who signs off on security
Tip: Ask about the work, not the technology. Who does it today, how long it takes, what a mistake costs, and how they'd know it got better.
- 4Ownership and working with customers
They wrote: “Ownership of high-impact projects across some of the world’s best companies.”
Tell me about something you shipped that broke in production.
How to answer
Why they ask: Everyone has broken production. They want to hear you own it and change something afterwards.
- What broke and who it affected
- How you found out and what you did in the first hour
- The root cause, said plainly
- What you changed so it can't happen the same way again
Tip: Pick a real one with a cost. Spend most of the answer on what you changed.
- 5Travel
They wrote: “Ability to travel - typically 10–50%, depending on the project, customer needs, and your role on the engagement.”
How do you handle being on the road with customers for weeks at a time?
How to answer
Why they ask: Many FDE roles involve regular travel. They check you know what you're signing up for.
- Your past travel or on-site experience
- How you stay productive away from the team
- What travel level works for you, said plainly
Tip: Be honest about what works for you. A mismatch here hurts both sides later.
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