AI Governance Specialist, Client Advisory

Location: Bangalore, India, with travel to client sites in Asia

Company builds AI-powered insurance and financial advisory platforms for insurers and banks. Our SaaS microservices and no-code/low-code technology let clients design, launch and run products faster, cutting time-to-market by up to 90% while reducing budget overruns and delivery risk.

We are a profitable B2B enterprise software company with presence in Singapore, Malaysia, Thailand and the Middle East, and we are scaling to the next level.

THE WORK CULTURE

AI is how we work. Every role at Company uses AI agents and tools every day to research, write, build, test and deliver. We hire people who use AI to multiply their output, and who still own the judgement and the result.

We are a lean, high-output team. Everyone owns outcomes, not tasks. We hold a high bar, move fast and do not promise what we cannot deliver.

We are fully remote. Work from wherever you do your best work. We judge output, not hours online, and we expect explicit, proactive written communication.

We hire for drive, hunger and real domain depth. Our hiring is selective, and we reward our people generously and fairly, including guaranteed bonuses.

What You Will Do

Company is advising a large Asian insurer through the selection and implementation of a group-wide AI governance platform across its markets. This role is the day-to-day delivery on that engagement, reporting to Company’s Head of AI Lab.

You will sit alongside the client’s control functions and their implementation partner and do the substantive work: reviewing vendor responses and architecture against the controls they have to carry, turning risk ratings and control catalogues into platform workflows and policy-as-code, running the sessions that get risk, compliance, cybersecurity, information security and vendor management to one agreed policy set, and building the intake and onboarding protocol for AI use cases and tools.

Everything you produce is a document a control function or a regulator will read. Clear,



plain writing is part of the job, not an afterthought.

Company works remotely, but this role is based in Bangalore at the client’s request, so that you can be at their offices when the engagement needs it.

Responsibilities

Policy and Controls

- Build the risk rating rubric with inputs drawn from the system where possible, rather than self-declared by the use case team.
- Draft the core policy set from the obligations that actually apply, and map each policy to the control that enforces it, the evidence that proves it and the function that owns it.
- Run working sessions with each control function and drive sign-off function by function.
- Translate the agreed policy into platform workflows and policy-as-code with the implementation partner.

Assurance and Monitoring
- Define the assurance framework: evaluations, guardrail verification, release gating and post-deployment monitoring.
- Define KPIs and thresholds per control, with the owner and the action that follows a breach.
- Produce written stage-gate findings at design, build and UAT on the vendor and partner’s work.

Adoption and Transfer
- Build the plain-language tiering and pre-approved patterns that let business teams self-serve.
- Train the control functions and business teams, and leave the material behind so onboarding continues without us.
- Keep the standing risk log and the lessons learned record current.

Requirements

Who You Are

- Credible in front of senior risk and compliance stakeholders, and comfortable being the Company person in the room.
- Precise in writing. Your documents are read by people who will act on them.
- Direct about what is thin,



including when the answer comes from a large vendor.
- AI-native: you already use AI tools to work faster and better, and you want to push that further.
- Willing to travel to client sites in Asia when the engagement calls for it.

What You Bring
- Built or run an AI use case inventory and intake process, including AI that arrives inside procured software.
- Owned a risk or materiality rating for AI use cases, and defended a rating to a control function.
- Written AI policies and mapped them to the controls that enforce them and the evidence that proves them, not policy drafting alone.
- Implemented or configured a governance or GRC platform: ServiceNow, Archer, OneTrust, Credo AI, IBM watsonx.governance or similar.
- Hands-on with guardrail and observability tooling: Langfuse, LangSmith, Dynatrace, Datadog, Azure AI Content Safety, Bedrock Guardrails or equivalent.
- Built evaluation suites, red-team exercises or regression testing for LLM or agent systems, and set the thresholds that decide pass or fail.
- Defined KPIs, thresholds and drift monitoring for systems already in production, and handled a breach.
- Worked to at least one of MAS, HKMA, EU AI Act, NIST AI RMF, ISO 42001, or model risk management under SR 11-7 style validation.
- Been through a platform implementation end to end, on the client side or the delivery side: selection, design, UAT, go-live.
- Bring an artefact to the interview: a rating rubric, a policy mapped to a control, an evaluation suite, a monitoring definition or a stage-gate finding. Redact what you must, but bring something real.

What Good Looks Like In The First Six Months

- The core policy set is agreed and signed off function by function, not still in draft.
- The platform enforces what was agreed, with evidence captured at each gate.
- A business team can find its tier and its obligations without asking anyone.

Skills: bedrock guardrails,ai governance,grc,langfuse,azure ai content safety,langsmith,dynatrace,datadog

📌 AI Governance Specialist (Bengaluru)
🏢 Arohana Tech Solutions Private
📍 Bengaluru