Senior Forward Deployed Engineer
Posted 2 days ago
The role in short
Embed with internal and external users to build, deploy, and optimize production AI agents and integrations for Lenovo's Qira platform.
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.
About Our Team
We are building Qira, Lenovo's next-generation cross-device Personal AI platform that delivers intelligent, context-aware experiences across Windows, Android, and the cloud. Our team takes Qira from platform to real-world use across Lenovo teams, consumer experiences, partner initiatives, and enterprise environments. We discover high-value use cases, build the integrations and agent capabilities that make Qira useful, and turn adoption learning into reusable product improvements.
About The Role
The Senior Forward Deployed Engineer is a hands-on software engineer who embeds with the people and organizations using Qira across Lenovo teams, consumer experiences, partner initiatives, and enterprise environments. You will build what each program needs, integrate it with the systems and devices people already use, and own the outcome from discovery through production adoption. This is a fully remote role with travel to Lenovo, partner, and customer sites.
Your initial focus will be leading priority Qira adoption programs, beginning with Lenovo’s “Customer Zero” program and potentially spanning consumer experiences, partner initiatives, and enterprise deployments as priorities evolve. You will engage senior business, product, and technical stakeholders as a credible technical peer, and bring what you learn in the field back into the product. This is an engineering role first. You write and ship production code, and you spend much of your time with the people who use it.
Location: US Remote, up to 25% travel
What You’ll Do
- Lead priority Qira adoption programs, beginning with “Customer Zero”: deploy, configure, and run Qira in real contexts, driving adoption and surfacing requirements from live usage.
- Embed with internal teams, consumer experiences, partner initiatives, and enterprise customers to map workflows, scope use cases, and turn ambiguous asks into deployable solutions.
- Write production code that ships into real environments: integrations, connectors, tool-using agents and skills, and MCP servers as the team’s standard integration pattern.
- Own deployments end to end across identity and SSO, device and app configuration, security and access review, and workflow integration, troubleshooting hands-on until they work in production.
- For enterprise deployments, engage CIO, CISO, and IT-administrator stakeholders on security posture, deployment models, integration patterns, and manageability.
- Define how each deployment is judged, including task success, safety, and adoption, and feed the results back to the product team.
- Support Qira launches, early-access programs, and use-case development across user segments, from beta cohorts to general availability.
- Turn repeatable deployment work into reusable components and patterns, and translate field requirements into engineering input that shapes the Qira roadmap.
- Mentor engineers and set the standards and playbook for how Qira is deployed.
Basic Qualifications
- 8+ years in software engineering, forward deployed engineering, solutions engineering, or applied AI, including significant customer-facing delivery.
- Proficiency in Python or TypeScript, with a track record of shipping production code.
- Shipped a tool-using LLM agent or LLM application to production, with hands-on experience in retrieval-augmented generation (RAG), prompt design, and evaluation.
- Independently deployed, integrated, and troubleshot software in customer or enterprise environments, including leading pilots or rollouts.
- Track record of driving adoption of what you built, not only delivering it.
- Experience engaging senior business, product, and technical stakeholders, including CIO, CISO, or IT leadership where applicable, on adoption, security, deployment, and integration decisions.
- Mentored engineers or set the technical standards for a delivery effort.
- Bachelor’s degree in a technical field.
Preferred Qualifications
- Enterprise identity and SSO (SAML, OAuth, OIDC, Entra ID, RBAC) and/or workflow automation and iPaaS platforms such as Workato.
- Strong communication skills, with the ability to explain technical decisions in plain language to business and executive audiences.
- Built reusable components that others adopted, such as an agent framework, MCP server, reference architecture, or deployment playbook.
- Taken a production deployment through a security or access-control review, including BYOC, on-prem, or data residency requirements.
- Built retrieval that respects source permissions over enterprise content (Microsoft 365, file shares, or similar).
- Experience with Windows, Android, or device management (Intune, Android Enterprise).
- Fluency in AI-assisted development workflows, with Cursor and Linear or equivalent tools.
What Success Looks Like
Qira capabilities running in production across priority programs, beginning with Customer Zero, with measurable adoption.
Clear success measures (task success, safety, adoption) defined and tracked for each deployment.
Deployments led independently, with core engineering engaged through defined channels for material product, security, and reliability needs.
Reusable deployment patterns and components contributed back to the product.
A repeatable deployment playbook that other engineers can follow.
The base salary range budgeted for this position is $190,000 - $210,000. Individuals may also be considered for bonus and/or commission.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
Prep for this interview
5 questions likely to come up at Lenovo, each matched to a line in this posting.
- 1LLMs, RAG and agents
They wrote: “Shipped a tool-using LLM agent or LLM application to production, with hands-on experience in retrieval-augmented generation (RAG), prompt design, and evaluation.”
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: “Proficiency in Python or TypeScript, with a track record of shipping production code.”
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.
- 3Integrations and APIs
They wrote: “Write production code that ships into real environments: integrations, connectors, tool-using agents and skills, and MCP servers as the team’s standard integration pattern.”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 4Cloud, deployment and security
They wrote: “Taken a production deployment through a security or access-control review, including BYOC, on-prem, or data residency requirements.”
A bank wants our product inside their own cloud account, with no data leaving it. How do you approach it?
How to answer
Why they ask: Self-hosted and private-cloud deployments are common in regulated industries.
- Learn their rules early: network limits, approved services, review process
- Package the product so it installs the same way each time (containers, Terraform)
- Plan how you'll get logs and updates without touching their data
- Run a test install with them before the real one
Tip: Talk about the conversation with their security team as much as the setup.
- 5Discovery and scoping
They wrote: “Lead priority Qira adoption programs, beginning with “Customer Zero”: deploy, configure, and run Qira in real contexts, driving adoption and surfacing requirements from live usage.”
Tell me about a time the customer asked for one thing but needed another.
How to answer
Why they ask: Good FDEs spot when a request is a guess at a solution. They want proof you can redirect a customer without losing their trust.
- What they asked for, and the detail that made you doubt it
- How you tested the doubt (shadowed users, looked at logs, ran a quick prototype)
- How you made the case to the customer
- What shipped and what changed for them
Tip: Pick a story where you checked your hunch with data or users before pushing back.
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