SVP, AI Scaling and Applied AI

Contactverse

India

A distancia

INR 3.000.000 - 6.000.000

Jornada completa

Hace 2 días
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Fully remote working
Company-provided equipment
Leadership opportunity
Direct access to founders

Descripción de la vacante

ContactVerse Galactic Labs Limited is seeking a senior engineering leader to own the AI platform and its deployment across India. You will manage orchestration, retrieval, and context, while controlling evaluation harnesses and ensuring safe, cost-efficient operation of production AI workloads.

The role emphasizes building and operating rather than researching, leading two directors, and shaping model usage, prompts, and the distribution of capabilities within the Core service.

Formación

  • Twelve years or more in engineering, including building and operating an LLM or multi-agent platform serving production traffic.
  • Has run evaluation properly (offline and online) and can describe a change that evaluation stopped.
  • Has made a production system materially cheaper without making it worse.
  • Deep understanding of retrieval, context management and the failure modes of both.
  • Has led engineers and at least one layer of management.

Responsabilidades

  • Own the AI platform: orchestration, tool use, retrieval and context management, serving production traffic.
  • Own evaluation: an evaluation harness and regression testing to prevent regressions.
  • Own the provider registry in practice: region-scoped provider selection with safe defaults and explicit fallbacks.
  • Own cost and performance: latency, throughput and cost per unit of work at scale, including cheaper models routing.
  • Apply models in product: agent behaviour and context corpus built in Core.
  • Own disclosure and safety in the product: ensure AI-drafted output is disclosed and agent actions are bounded.
  • Lead two directors: Scaling and Applied AI, and Data and Analytics.
  • Keep the context corpus current and version-controlled.

Descripción del empleo

This is the role that makes AI work at ContactVerse in practice.

Location India, Remote

Job ID POS-008

Posted Oct 14, 2026

About the role

This is the role that makes AI work at ContactVerse in practice. We route every AI request through a Core service against a region-scoped provider registry (India runs a different speech and language stack from Europe) and the industry verticals call Core rather than calling a vendor. You would own that platform and the application of it in product: orchestration, retrieval, context management, evaluation, latency, throughput and cost. It is a build-and-operate role, not a research one.

What you will do
  • Own the AI platform. Orchestration, tool use, retrieval and context management, serving production traffic through Core.
  • Own evaluation. An evaluation harness that tells us whether a change helped, and regression testing of model behaviour so that an improvement in one place is not a regression in another.
  • Own the provider registry in practice. Region-scoped provider selection, with a loud fallback: substitute a safe default and raise an event rather than failing the request or silently doing something else.
  • Own cost and performance. Latency, throughput and cost per unit of work at the scale our plans promise, including routing routine work to cheaper models.
  • Apply models in product. Agent behaviour, prompts and the context corpus behind them, built once in Core rather than vertical by vertical.
  • Own disclosure and safety in the product. Where output is AI-drafted, the disclosure evaluation runs before send. Where an agent acts, the boundary of what it may do without a human is explicit.
  • Lead two directors. Scaling and Applied AI, and Data and Analytics.
  • Keep the context corpus current. When a model gets something wrong we fix the context it works from, under version control, not the single output.
  • Work with the Chief Architect. So that no industry vertical ever calls an AI vendor directly. That rule is not advisory.
Your first year

First 90 days. An evaluation harness that tells us whether a change helped, and a baseline for cost per unit of work.

By six months. The platform serving production traffic through Core, with routing policy in force and costs falling.

By twelve months. AI capability the product team can use without asking you how.

What you will bring
  • Twelve years or more in engineering, including building and operating an LLM or multi-agent platform serving production traffic.
  • Has run evaluation properly (offline and online) and can describe a change that evaluation stopped.
  • Has made a production system materially cheaper without making it worse.
  • Deep understanding of retrieval, context management and the failure modes of both.
  • Has selected providers against real workloads, by region, and lived with the consequences.
  • Has led engineers and at least one layer of management.
  • Pragmatic about research: we apply models, we do not train them.
  • Comfortable with ambiguity in a product that is still being defined.
Nice to have
  • Speech (ASR and TTS) as well as text. We run voice agents.
  • Experience of Indian language models or speech stacks.
  • Cost engineering across multiple providers and buying channels.
  • Agent frameworks and tool-calling architectures at scale.
  • Experience of a regulated or compliance-sensitive domain.
What you will work with

Python and FastAPI on AWS, a Core service mediating all AI calls, a region-scoped provider registry, vendor credentials in AWS Secrets Manager, and a documentation site generated from the requirement sheet. India runs Sarvam and Krutrim; other regions differ.

What this role is not

Not a research lab. We are applying models, not training them, and the measure is what ships.

How we work

The team works to a UK-aligned pattern, with the main working overlap in the evening IST. These hours are indicative and may change as the business changes; any change would be discussed rather than imposed. Development happens on company-provided remote machines. Everything is remote and nobody is in an office.

We are a small company and we write things down. Decisions are recorded, corrections are made to the source rather than to the output, and status is expected to be honest even when it is unwelcome.

Compensation and what we offer
  • A long-term incentive, discussed at offer stage for senior appointments.
  • Fully remote working, with company-provided equipment where the role requires it.
  • A role with unusual scope for its level, because the organisation is being built rather than joined.
  • Direct access to the founders. There are no layers between this role and the people making the decisions.
How we will assess you

We assess against three or four weighted signals agreed before we read a single CV, rather than against years of experience or a list of tools. Expect four stages:

  • Introductory conversation with our People team. About 30 minutes, covering the role, your background and what you are looking for. This first conversation may be with an AI assistant; you will be told at the time and may ask to speak to a person instead.
  • Conversation with the hiring manager. About 60 minutes, going deep on what you have done and how you think.
  • A working session on a real ContactVerse problem. About 90 minutes. Not a whiteboard exercise and not a take-home test you do unpaid in your evenings.
  • Final conversation with the founders. Covering fit, expectations and how we would work together.

We aim to complete the process within three weeks and to give you a decision, with reasons, within three working days of the final stage.

Equal opportunity

ContactVerse is an equal opportunity employer. We welcome applications regardless of age, disability, gender identity or expression, marital or civil partnership status, pregnancy or maternity, race, religion or belief, sex or sexual orientation. We select against the published signals for the role and nothing else. If you need an adjustment at any stage of the process, tell us and we will make it. It will not count against you.

Research consistently shows that some candidates apply only when they meet every criterion.

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