---
title: 'Forward-Deployed AI Architect at Neurons Lab'
canonical: 'https://feeny.ai/job/forward-deployed-ai-architect-neurons-lab-italy-68p1xkqt2d6s'
type: 'job'
last_seen: '2026-10-20'
---

# Forward-Deployed AI Architect at Neurons Lab

- **Company:** Neurons Lab
- **Location:** Italy
- **Employment:** contract
- **Work type:** remote
- **Posted:** 2026-10-20
- **Last confirmed live:** 2026-10-20
- **Apply:** https://jobs.ashbyhq.com/neurons-lab.com/2c212d0d-c3c3-411d-bfd2-12b2b38d8c56

## Job description

## About the role

We are looking for a hands-on Forward-Deployed AI Architect to lead the technical delivery of an AI-assisted operations platform for an enterprise client in travel disruption management. The current phase covers three connected workflows:

- Processing and routing service requests
- Ranking and recommending hotels
- Closing cases with billing reconciliation and downstream system handoff

You will turn operational knowledge and existing software into a working, testable system with explicit human approvals and traceable decisions. This is technical leadership, not architecture-only advice or task execution. You will work directly with operational experts, the client’s technology partners and our engineers, challenge assumptions constructively, and carry the technical solution from discovery through implementation and evaluation.

## How you will work

You own the technical approach, engineering plan, implementation quality and evidence of readiness. You partner with the engagement Principal, who owns the integrated delivery plan, commercial scope and client commitments. You provide feasibility assessments before commitments are made and escalate unresolved dependencies or scope changes with options and their impact.

## What you will own

1. Establish an evidence-based technical baseline

- Inspect the code, infrastructure, APIs and operator workflows before estimating the build.
- Translate discovery into concise specifications with inputs, outputs, exclusions, acceptance tests and source references.
- Distinguish confirmed requirements from analyst recommendations and assumptions.
- Resolve contradictions with the appropriate owner. Do not implement them silently.

1. Make integration work early

- Build and review critical components, guide engineers and prove a thin end-to-end path in the client’s test environment: receive a request, retrieve operational data, produce a recommendation, obtain approval and perform the agreed system handoff.
- Verify API access, write capabilities, event contracts and error paths. Do not treat documentation or isolated components as proof of readiness.

1. Make rules and knowledge maintainable

- Design a clear separation between operational facts, business policies and software logic.
- Work with named business owners to define rule precedence, exceptions, validation and approval.
- Keep draft or inferred rules separate from approved rules.
- Support versioned updates without a software release, with historical replay, traceable approval and rollback.
- Use grounded reasoning and human escalation where rules do not resolve a case.

1. Own engineering quality and evaluation

- Review and test code, including AI-generated code, against the agreed architecture.
- Establish automated CI checks, integration tests and representative operational cases.
- Track the exact application, rule and data versions evaluated.
- Implement decision logs, monitoring, access controls and failure recovery.
- Define test-readiness evidence and agree workflow-quality, latency and operating-cost measures with the team and client.

1. Keep technical decisions and progress clear

- Maintain a concise architecture and decision record that shows what works, what remains and why.
- Raise blockers early with evidence, an owner, a decision needed and delivery impact.
- Propose simpler alternatives and update estimates when assumptions change.
- Demonstrate working increments, and clearly distinguish prototypes from integrated functionality.
- Leave the team with maintainable code, documentation and a practical handover.

What good looks like

- Before build commitments: a reviewed technical baseline, verified critical dependencies and explicit assumptions behind the estimate.
- During delivery: a working end-to-end increment, automated tests running in CI, and demonstrated progress against agreed acceptance cases.
- For rule changes: a named business approver, a versioned baseline and recorded replay results before promotion.
- At evaluation: reproducible results, decision traces and documented limitations that support the agreed Go/No-Go decision, not just a successful demo.

Specific targets will be agreed after the baseline is established. You will stay involved from the initial working sessions through delivery and evaluation.

## What you bring

- Evidence of taking an applied AI or LLM-enabled workflow beyond a prototype into operational use.
- Strong hands-on software engineering, architecture, API integration and code-review skills.
- Experience turning incomplete or conflicting discovery material into implementable, testable specifications.
- Sound judgment about structured rules, retrieval, AI reasoning and human review, including their failure modes.
- Practical experience with evaluation datasets, regression testing, CI and production observability.
- Confidence to challenge assumptions, explain alternatives and escalate decisions constructively across business and engineering teams.
- Clear, concise communication and realistic estimation based on verified dependencies and available capacity.

## Nice to have

- Experience in exception-heavy operations, business-rule systems, travel, hospitality or logistics
- Familiarity with AWS-based AI deployments

Logistics The role includes an in-person working session in Milan. Please share your earliest start date, realistic weekly availability and ability to travel.

## About Neurons Lab

## Company Overview
- **One-liner**: Neurons Lab is an AI engineering partner that helps Financial Services organizations adopt AI and build production-grade agentic systems, from initial use case definition through deployment and continuous delivery.
- **Entity Type**: Private (Bootstrapped / Self-funded boutique firm)
- **Headquarters**: London, United Kingdom (International House, 64 Nile Str, London, N1 7SR)
- **Founded**: 2019
- **Founders**: Igor Sydorenko (CEO & Co-Founder) and Alex Honchar (CTO & Co-Founder)

## Core Business
- **Primary industry/industries**: AI Engineering & Consulting, focused exclusively on Financial Services (banking, capital markets, wealth management, insurance)
- **Target customers**: B2B — Fortune 500 financial institutions, large banks, wealth management firms, insurance companies, and adjacent regulated industries
- **Mission or purpose statement**: To help Financial Services organizations move from AI-curious to AI-enabled by building capability and deploying systems across core workflows — translating AI ambition into secure, scalable solutions that deliver commercial value.

## Products & Services
- **Custom AI Agents**: Deploy custom AI agents from discovery through production, enabling automation across core workflows with full auditability, traceability, and governance controls built in from the start. Decision logic is aligned with business rules and policies, designed for high-value workflows where accuracy, compliance, and scale are critical.
- **AI Training & Enablement**: Build AI fluency across teams, from engineering to the C-suite, through hands-on training grounded in the client's core workflows. Separate tracks for business and technical teams, with governance, compliance, and risk embedded from the start.
- **Continuous AI Delivery**: Post-deployment support with Forward-Deployed Engineers working alongside client teams to ensure systems continue to evolve. Governance, monitoring, and performance tracking are built in from the start, with AI adoption compounding across workflows over time.

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private, self-funded boutique firm)
- **Key Metric**: Total Funding — Not disclosed (bootstrapped); the team reports 100+ AI implementations since 2019, including with Fortune 500 firms, and a team of 50+ AI engineers, architects, and analysts across Europe
- **Notable Investors/Partners**: Anthropic (partner), AWS (Advanced Partner, among first 15 to achieve AWS GenAI Competency in Agentic AI), Google Cloud (Partner)
- **Growth Signals**: Achieved AWS AI Competency in the Agentic AI category; named clients include HSBC (aligned 50+ senior leaders on AI deployment and governance) and Visa (scaled marketing operations across 9+ markets with LLM-based content system); works with leading Asian banks on agentic AI assistants for relationship managers

## Competitive Advantages
- **FSI Domain Expertise**: Deep specialization in Financial Services (banking, capital markets, wealth management, insurance) means no translation layer between business intent and technical execution. Compliance, governance, and risk are built into system design from the start.
- **Embedded Co-Creation**: Unlike traditional consultancies, they co-create with client teams through embedded delivery, working alongside internal stakeholders to transfer knowledge and expand impact from inside the organization.
- **Accelerated Delivery**: Pre-built FSI agent components and proven deployment patterns allow delivery of working, production-grade systems in weeks rather than months.
- **Boutique Senior Teams**: Small, senior teams (50+ engineers/architects) rather than large junior-heavy teams, enabling high-quality, fast execution.

## Strategic Focus
- Expanding agentic AI adoption within regulated financial environments, focusing on production-grade systems that operate within existing governance frameworks
- Building on partnerships with Anthropic, AWS, and Google Cloud to deliver cutting-edge AI solutions
- Deepening presence in wealth management, retail/corporate banking, private banking, SME banking, and insurance segments
- Scaling through a two-tier talent model (Core Team + Talent Network) to remain agile while growing

## Why Work Here
- **Remote-first culture**: Work from anywhere, with flexible hours — "design your day" philosophy
- **Benefits**: Unlimited PTO, flexible schedule, work on projects incorporating the latest AI technology (Anthropic, AWS, GCP)
- **Culture**: 7 guiding principles including ownership, genuine connections, and leadership development. Small, senior teams with high autonomy and low bureaucracy
- **Growth**: Opportunity to work on cutting-edge agentic AI for Fortune 500 financial clients, with clear paths to leadership roles
- **Team structure**: Two collaboration options — Core Team (full-time, benefits-eligible) or Talent Network (project-based, minimum 0.33 FTE)
- **Interview process**: Fast, streamlined — application → screening interview → validation interview → qualification interview → reference check

## Sources
1. [neurons-lab.com](https://neurons-lab.com/about/)
2. [neurons-lab.com](https://neurons-lab.com/)
3. [neurons-lab.com](https://neurons-lab.com/careers/)
4. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/neurons-lab.com)
5. [neurons-lab.com](https://neurons-lab.com/careers/core-team/)

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