Skip to content

Open nowFirst seen 42 hours ago

Agentic AI Architect / Generative AI Architect

newbridge101 open roles

Where
Singapore
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowAgentic AI Architect / Generative AI Architectnewbridge · Singapore
  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on newbridge's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 42 hours ago

The posting

A major US multinational is expanding its Data & AI consulting practice out of Singapore. They are hiring a practitioner-architect to be the technical owner for all client AI deliveries.

You will be the most senior hands-on architect in the team and the go-to technical face for clients. Your job is to decide how we build - when to go agent-first and when to keep it simple and deterministic - and to make sure what we build is secure, governed, production-ready and defensible to risk, security and audit teams.

You will work with a small build team in Singapore [AI Engineers, Data Engineer, Data Scientists], partner with global Data & AI and Controls teams, and sit across the table from CTOs, CDOs, Enterprise Architects and CISOs/CROs.

What You'll Do

1. Lead Architecture for Client Builds Define the target architecture from problem framing to live production. Convert business use-cases into clear blueprints - components, data flow, model choices, integration approach, security and governance. Create reusable reference architectures for both enterprise AI and agentic systems - multi-agent workflows, A2A and MCP tool layers, gateway patterns, RAG / knowledge systems, and enterprise integration. Set the standard for when agentic actually helps vs when it doesn't.

2. Own Platform, Model & Risk Decisions Own the model/vendor strategy. Evaluate and compare frontier closed models and open-weight models on performance, cost, latency, context, residency, security and portability. Build evaluation criteria, selection guardrails and exit strategies so clients don't get locked in. You own the build-vs-buy call.

3. Bake in Security, Controls & Governance Design with controls on day zero - injection safeguards, least-privilege agent identities, tool permissioning, sandboxing, human-in-the-loop, DLP, memory integrity, sovereignty, audit trails and evidence. Make sure designs can pass muster with regulated clients, boards and regulators across APAC.

4. Set the Technical Bar for the Practice Define architecture principles, patterns, NFRs, and design review / assurance rituals. Review engineering work, mentor the team, and raise overall quality. Partner with practice leadership to shape proposals - technical approach, delivery plan, risk stance - and build reusable assets, accelerators and methods.

What We're Looking For

  • 6-10 years in solution / enterprise / data / cloud / AI architecture or consulting, with real experience shipping production AI / data / platform systems.
  • Proven track record building production GenAI and agentic systems end-to-end - orchestration, retrieval, model integration, enterprise systems, and moving from POC to prod.
  • Comfortable as the client-facing technical lead - running architecture workshops with senior enterprise stakeholders.

Strong Advantage If You Have:

  • Deep agentic expertise - multi-agent orchestration, A2A, MCP, gateways, RAG, vector stores, knowledge graphs, evals.
  • Hands-on with frameworks like LangGraph, CrewAI, AutoGen, Microsoft Agent Framework or similar.
  • Good understanding of model landscape - Anthropic / OpenAI / Gemini + Llama / Gemma / Phi / Mistral / Cohere and how to pick between them.
  • Exposure to APAC models - Qwen, DeepSeek, GLM, Kimi, Yi, HyperCLOVA X, EXAONE, ELYZA, SEA-LION etc.
  • Strong on cloud AI stacks - Azure [Foundry / AOAI], AWS Bedrock, GCP Vertex - plus knowledge of sovereign clouds for residency - Alibaba, Tencent, Huawei, Naver, self-hosted inference.
  • Solid integration design - APIs, events, identity, enterprise apps, data platforms - plus MLOps / Lakehouse / observability.
  • Security for AI systems - injection defense, tool auth, identity, approvals, audit, privacy.
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against newbridge's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.
  3. We apply on newbridge's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.
  4. Every reply, sorted

    newbridge's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.
  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.