Forward Deployed Engineer

About Us

Praxis Intelligence Pte. Ltd. is a Singapore-based company that takes enterprise AI from strategy to production. Through our consulting and deployment practice, NextAI+ Praxis, we work with enterprises from use-case discovery through solution design, system build and go-live, and we stay through the stage where most AI programmes stall: integration with real data, real systems and real people. Current engagements span maritime, e-commerce, semiconductors and electronics, and traditional energy and manufacturing.

We are not a pure consultancy. The practice is supported by our own AI infrastructure layer, an enterprise platform for governed model access, routing and cost attribution across providers and clouds, together with a set of internal build tools that take us from a client interview to a working system in short order. Client deployments run on this foundation, and what we learn in the field feeds back into it.

Enterprise AI rarely fails on the model. It fails on data nobody can locate, access nobody can grant, and compliance questions nobody in the room can answer. This role exists to be the person in the room who can.

The Role

You sit between our clients and our build team, and you work in both directions.

In the consulting phase, you join client interviews, workshops and site visits. When the client asks what is technically feasible, what their data actually allows, or how a design holds up against their compliance obligations, you answer, on the spot and credibly.

In the build phase, you help design and build what the engagement calls for: prototypes and proofs of concept, agent workflows, data pipelines, dashboards, and the evidence base behind our proposals. You carry what you learned on the client side into what gets built.

• Run technical discovery. Map the client's data landscape: what exists, where it lives, who may access it, what shape it is in. Turn business needs into technical scope with clear interfaces, data structures and acceptance criteria.

• Own the compliance posture of the solution. Identify the constraints that apply (PDPA, data residency and cross-border transfer, sector rules such as MAS guidelines for financial clients, client-internal security policies) and shape the design within them. Explain the posture to a client's IT, legal and business stakeholders in their own terms.

• Build. Prototypes, POCs, agent workflows, integrations with client systems and databases, data processing, dashboards. On our platform and inside client environments, including private and on-premise deployments.

• Scope and review data science work. Know what a data scientist does well enough to scope it, review it, or do a lighter version yourself: framing the problem, assessing data readiness, judging an evaluation, telling a validated result from a convincing demo.

• Build the case. Help assemble the case studies, benchmarks, demos and architecture material that back our proposals and our public case showcase.

• Document. Technical notes, architecture sketches, interface specs and deployment guides, for us and for the client.

Requirements
• 1–3 years in software engineering, data engineering, data science or solutions engineering, with

real production or client-facing work behind you.

• Proficient in Python and SQL; comfortable in at least one of TypeScript or Go.

• Working knowledge of data security and data compliance. Access control, encryption basics, data residency, PDPA, audit trails. You do not need to be a compliance officer; you need to hold a credible conversation about a client's data concerns and design accordingly.

• A clear understanding of the data scientist's role and workflow. Problem framing, data preparation, model evaluation and validation. You can read an evaluation and know what it does and does not show.

• Hands-on LLM application experience. Tool calling, retrieval, structured outputs, prompt and workflow design. You use coding agents daily and have a view on where agents are and are not reliable.

• Solid engineering fundamentals. Database and API design, system integration, Docker, Linux, Git.

• Full professional proficiency in English, written and spoken. You explain technical matters clearly to technical and business audiences alike, hold your own in a client meeting without a script, and write documentation people actually read. Strong interpersonal skills; this role is as much about conversations as it is about code.

• Comfortable with ambiguity. Able to move forward with incomplete information and shifting requirements.

Nice to Have

• Cloud deployment experience (AWS, GCP, Azure or Alibaba Cloud) and CI/CD

• Data visualisation and dashboard design

• Deep, hands-on experience with the data of one specific industry, whichever it is. We do not need you to have worked in our current sectors; we value people who know what one vertical's data actually looks like and can bring that discipline to another. Varied backgrounds are a strength on this team, not a gap to explain.

• Pre-sales or solutions engineering background
• Familiarity with industry compliance beyond data (workplace safety, financial regulation, and the like)

Who We Are

We are small and early. A fair amount is still being decided: how we sell, how we deliver, which bets we double down on. The people who join now will decide a good part of that with us. This is not a place where the role arrives fully defined; it is a place where the role grows with what you show you can carry. If that reads as both exciting and a little uncertain, that is an accurate description.

Compensation

Competitive for an early-stage company in Singapore, and structured so that the people who build the company early share in what it becomes. Beyond the package: ownership of real client systems from your first engagement, exposure to how enterprises in several industries actually run, and a team that works hands-on with frontier AI tooling every day.

How We Work

Location Work mode Travel

Apply

Singapore Hybrid

Periodic: client sites in Singapore and internationally for discovery, integration, go-live and training

Email hr@nextaipraxis.com with:

• CV — PDF, please state the position you are applying for.

• Work or code links — GitHub, project pages or live systems.

• A short note — one technical problem you solved for a non-technical stakeholder, and how you explained it to them.