Forward Deployed Engineer – Applied AI & Search

About ChapsVision & Sinequa

We build the enterprise platform for AI-powered search and agentic orchestration. The goal is straightforward: give every employee fast governed access to the right information in the right context when they need it with tight control over how AI uses it.

As part of the North America Professional Services team youll be the Forward Deployed Engineer (FDE) embedded on-site with one of our largest and most strategic customers a global manufacturing leader running a multi-year co-innovation program to put agentic AI in the hands of its workforce at scale. Its a hybrid role: business lead and technical lead in one. Youll own the translation of the customers priorities into Sinequa delivery and of platform capability into outcomes its teams actually adopt. Youll build production-grade applications help shape the platform roadmap from the field and work across the customers stakeholders its embedded delivery team and our R&D group.

What Makes This Role Different

A lot of forward-deployed roles give you a set playbook and a rotating list of accounts. This one is set up differently.

Youll own a single flagship account from start to finish building against real production data (drawings specifications parts PLM) rather than demo environments. And because this is the deployment that shapes how we scale what you work out here will become the blueprint for the next wave of strategic customers. The strongest parts of what you build can make their way into the core platform roadmap so your field work reaches every customer we have.

Youll have real ownership of the account with the platform the R&D relationships and company resources behind you.

What You Will Do

Embed with the customer: Sit on-site at the customers headquarters working day-to-day with its business stakeholders its own program team and technical leadership. Youll be the main point where account strategy and technical delivery come together.

Translate in both directions: Turn business priorities into a delivery plan you can actually build and turn platform capability into outcomes that work for the people using them. A lot of the value here is judgment and translation not just code.

Lead technical discovery: Run the architecture discussions whiteboarding and discovery needed to map a complex data ecosystem across PLM drawings specifications and parts data spanning several business units.

Resolve blockers at the desk: Work through a rigid enterprise environment with high interpersonal instincts. Youre comfortable walking over to a stakeholders desk to unpack an integration roadblock and get people to agreement.

Build Governed Agentic Workflows & Search Solutions

Ship production artifacts: Write clean production-grade code for complex components like Model Context Protocol (MCP) servers stateful sub-agents and deterministic agent skills on our agent orchestration platform.

Model-agnostic design: Build workflows that use the right frontier LLM for the job (Claude Gemini GPT or specialized open-source models) tuned for cost context limits and latency.

Optimize search at scale: Manage high-scale indexing and search pipelines for a user population in the tens of thousands. That means search-engine performance work document chunking and real-time relevancy tuning across a range of data silos including the PLM-sourced technical content (for example PTC Windchill) that sits at the core of this program.

Build in strong guardrails: Design clear process guardrails and required Human-in-the-Loop (HITL) checkpoints including SME validation role-based access and a capability maturity lifecycle so autonomous agents working in low-margin-for-error settings stay safe predictable and auditable.

Bridge Delivery and R&D and Scale the Product

Bridge PS and R&D: Sit between Professional Services delivery and core R&D. Carry escalation authority and roadmap visibility and route what you find in the field into structured product feedback.

Accelerate the handover: Bring the product depth that helps the customers embedded team take over more of the work over time. Part of doing this job well is gradually handing it off so their team can run it without you.

Champion safety & reliability: Keep a high bar for data privacy making sure native enterprise document-level permissions hold up end-to-end through the retrieval and AI execution loop.

You May Be a Good Fit If You Have

Agentic platform depth: Hands-on experience with agentic platforms and agent orchestration matters most for this role. If youve done this kind of work before youll get up to speed faster. If you havent well want to see that youve ramped quickly on complex proprietary platforms in the past.

A proven track record (8 years): Time in a highly technical customer-facing role such as Forward Deployed Engineer Solutions Engineer or client-facing Software Engineer. We care more about what youve shipped and the trust youve earned than the exact number of years. Former technical founders are also highly encouraged to apply.

Account-leadership range: You can run a strategic account relationship not just close out tickets. You can talk governance risk with a Director in the morning and debug a retrieval pipeline with a developer in the afternoon and hold your own in both rooms.

Production programming: Solid production-grade proficiency in Python and C# with working TypeScript for front-end integration and clean maintainable code. We value judgment translation and account leadership as much as raw coding speed.

Production AI experience: Youve shipped AI-powered systems in the real world things like prompt engineering agent development evaluation frameworks and deployment at scale not just prototypes.

Search & retrieval expertise: Deep practical experience with enterprise search engines relevancy tuning and vector databases (for example Elasticsearch OpenSearch Pinecone). You can diagnose and tune precision and recall and re-ranking pipelines when a query misses.

Production agentic orchestration: Hands-on experience building stateful multi-agent workflows managing context windows and wiring up structured tool-calling and API integrations with modern frameworks (for example LangGraph AutoGen CrewAI LlamaIndex).

Manufacturing domain depth & PLM: Experience in manufacturing settings indexing very large structured and unstructured enterprise document lifecycles. Direct experience with PTC Windchill is a real advantage.

High-context communication: You can move comfortably between deep technical debugging with developers and higher-level risk-focused conversations with corporate directors and compliance officers.

How We Work With AI

Were an AI company and AI fluency is part of how we work day-to-day not a side skill. Youll use frontier models regularly to move faster and do better work and wed like you to have a point of view on where AI helps and where it gets in the way. The interview includes a short practical AI exercise so we can see how you think about designing and using it. Bring whatever tools and workflows you already use; theres no single right way to do it.

Why Join Us

Real measurable impact: Youll work on a program where our agentic platform already does better than the in-house tools it replaced on data that general-purpose AI cant reach.

Real ownership: Youll own the technical relationship with a global manufacturing leader and have the room to decide how the work gets done with the platform behind you.

A direct line to the platform: Youll work closely with our core Product and R&D teams and what you learn in the field feeds into what we build next.

Hard interesting work: Productionized agentic architectures model-agnostic systems and governed enterprise AI at global scale.

We offer a full benefits package: medical dental and vision coverage a 401(k) plan a generous time-off policy and annual learning and wellness stipend.

Working Conditions

Location: On-site at the customers headquarters in the U.S. Midwest (Columbus Indiana area). Typically four days on-site and one day remote. Local residence or relocation is required.

We are currently unable to consider candidates who require or will require in the future sponsorship for work authorization. Applicants must be authorized to work in the US on a permanent and ongoing basis without the need for current or future employer-sponsored work authorization.