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Indicium AI

End-to-end data and AI consulting

Principal Forward Deployed AI Engineer

AI Application EngineeringUpdated on Oct 29
Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

  • You have taken AI systems from ambiguous problem to production deployment, including agentic systems, retrieval architectures and evaluation frameworks, inside a real organisation with real constraints.
  • You have owned the technical direction of a project or workstream, made the architecture calls, and been accountable for the decisions made.
  • You are genuinely hands-on, write production code rather than only reviewing it, and are comfortable pairing with an engineer.
  • You have led a delivery team through planning, sequencing, unblocking, and communicating project status clearly.
  • You have been the technical face of a piece of work, including when it was going badly.
  • You have grown other engineers deliberately through mentoring, coaching or review.
  • You have navigated large-organisation constraints including security reviews, compliance, legacy systems, and multiple teams with different incentives.

Responsibilities

  • Own the technical direction of complex AI engagements or multiple concurrent engagements, make architecture decisions, and be accountable for their production performance.
  • Set architectural patterns for agentic systems at scale, including state and memory design, failure modes and recovery.
  • Design and build production agentic AI systems, including multi-agent orchestration, autonomous agent workflows, tool-use patterns, and reliability layers for regulated environments.
  • Build advanced retrieval-augmented generation pipelines, including retrieval architectures, embedding strategies, reranking, hybrid search, and evaluation frameworks.
  • Develop and deploy Model Context Protocol servers and tool ecosystem integrations within enterprise infrastructure.
  • Design evaluation and observability frameworks for non-deterministic systems so production AI applications are measurable, debuggable, and continuously improving.
  • Deliver workstreams through Lead and Senior Forward Deployed Engineers, using reviews and course corrections to keep work on track.
  • Be accountable for delivery quality across engagements, including outcomes, timelines, scope, burn, and margin.
  • Manage senior client stakeholders and act as a trusted advisor to client technology leadership, helping shape roadmaps beyond the current engagement.
  • Influence new business wins through pre-sales, technical points of view, proposal shaping, and partner relationships.
  • Develop Senior and Lead Forward Deployed Engineers and shape coaching and learning and development across the technology practice.
  • Create intellectual property, accelerators, and reference architectures that improve engagement speed and margin.
  • Help develop the business through internal initiatives.
  • Work alongside Anthropic field teams on joint client engagements and represent Indicium AI at a senior level.

Desired Qualifications

  • A consultancy background and understanding of consultancy commercial models and client relationships.
  • Depth in Financial Services, Energy, or Healthcare sufficient to be a credible peer rather than a technology generalist.
  • Experience contributing to commercial shaping or estimating.
  • Model Context Protocol server development and enterprise tool ecosystem integration.
  • Prompt and context engineering, guardrails, and production large language model safety patterns.
  • Experience as a technical founder who built something from nothing under commercial pressure.
  • Writing, speaking, or community presence in AI engineering.
  • Experience working alongside partner ecosystems such as Anthropic, Databricks, or AWS.

About the Company

Indicium AI

End-to-end data and AI consulting

Indicium AI provides end-to-end data and AI consultancy for mid-size and large enterprises, helping organizations organize data, design data strategies, build data platforms, and enable AI adoption. They work by applying the Modern Data Stack (AWS, Databricks, Google Cloud, Snowflake) to deliver data solutions, and they use IndiMesh, a proprietary AI-enabled framework with pre-built templates and governance processes, plus AI Data Squads that combine human experts with AI agents for complex migrations. They differentiate themselves through scalable, service-based delivery using a repeatable framework rather than a single product, focused on standardizing and accelerating large-scale data and AI programs, and by expanding their operations in the United States. Their goal is to help enterprises improve data-driven decision-making and scale AI adoption across industries and geographies.

Company size
201-500
Company stage
Late Stage VC
Total funding
$40M
Headquarters
Palhoça, Brazil
Founded
2017

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