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DevOps Engineer (remote preference is California based)
Cansel Group of companies
Ventura, CA · Anaheim, CA · Pleasanton, CA · Fresno, CA · Sacramento, CA
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GTM Engineer
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San Francisco, CA
- $140,000 to $180,000 USD / year
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Founding Fullstack Engineer
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- $160,000 to $250,000 USD / year
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AI Connect Principal Project Management Engineer
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- $120,500 to $231,000 USD / year
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Software Engineer, Product - Deployments
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Instrumentation Engineer
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Lead and manage the execution of Instrumentation scope of work at the selected engineering service provider in all phases (Pre-FEED, FEED, and Detail Design).
Added 4 mins ago
W
Lead AI Engineer
WTW
NY
- $100,000 to $350,000 USD / year
…of the Fortune Global 500? We are looking for an exceptional engineer to join our Willis Neuron Technology team in New York or London as Lead AI Engineer: a senior, high-autonomy individual…
Added 5 mins ago
Civil/Environmental Engineer
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Sr. Field Service Engineer
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L2/L3 Network Technical Support Engineer – Broadband
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Senior Network Engineer
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Senior Systems Engineer-WP-AFB 1
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Added 12 mins ago
W
Lead AI Engineer
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- $100,000 to $350,000 USD / year
…of the Fortune Global 500? We are looking for an exceptional engineer to join our Willis Neuron Technology team in New York or London as Lead AI Engineer: a senior, high-autonomy individual…
Added 12 mins ago
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WTW

Lead AI Engineer

New York, NY, United States
NY, United States

$100,000 to $350,000 USD / year

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Job details

Pay: $100,000 to $350,000 USD / year
Posting language: English
Posted: Nov 9, 2026

Original job description

Would you like to apply the leading edge of AI to some of the hardest problems in risk and insurance, inside a global company that works with 91% of the Fortune Global 500? We are looking for an exceptional engineer to join our Willis Neuron Technology team in New York or London as Lead AI Engineer: a senior, high-autonomy individual contributor role in technology delivery, for someone already working at the frontier of AI engineering. You will work like a forward deployed engineer, as part of our delivery team rather than apart from it. Alongside brokers, actuaries, catastrophe modellers, architects and fellow engineers, you will get close to the real problem, prove what is possible in days, and then see it through to an industrialised solution: secure, tested, observable and supportable on our shared platform. This is not a line management role. We are looking for exceptional personal productivity and judgement: strong enough to deliver on your own, and collaborative enough to make the team around you better. Our delivery model is pivoting towards AI agent-led development, and we are building agentic analytics, MCP services and AI-enabled products on a rich estate of risk data and models. You will keep pace with the field and have the standing to decide what is worth adopting.

The Role

Work as a forward deployed engineer within our delivery team: get close to brokers, actuaries, modellers and clients, and build AI solutions that differentiate WTW in the market, wherever they add the most value across R&A and Data.
Prove ideas fast, with working software in days, then industrialise what works: take it through our delivery pipeline (backlog, code review, CI/CD, QA and release) into secure, supportable production services, handed over cleanly to service teams.
Design and build agentic analytics and AI-enabled products using large language models, RAG, MCP and modern agent frameworks, as reusable components and services on our shared platform rather than one-off solutions.
Own the quality bar for AI in production, including evaluation, testing, guardrails, observability, security and cost management, so that AI answers over risk data can be trusted by clients and colleagues.
Bring analytical rigour and domain depth: apply your quantitative background and your understanding of insurance, exposure, loss and catastrophe modelling to build solutions that stand up to scrutiny from actuaries and modellers.
Deliver as part of a team: plan and prioritise with Delivery Leads and Product Leads, and shape the technical direction for AI with Product Architects, within our architecture, security and compliance standards.
Direct AI coding assistants and agentic workflows (e.g. Claude Code, GitHub Copilot) alongside your own hands-on expertise to multiply your output, and rigorously review human-written and AI-generated code against our standards.
Lead by example, without line management: raise the standard through the quality and pace of your own work, mentor colleagues informally, and share what you learn so capability spreads across the team.
Stay at the frontier: track new models, tools and techniques, test them hands-on, and bring the credible ones into our roadmap and delivery approach.

The Requirements

Essential:

10+ years of professional software engineering experience, in any modern stack, with a record of leading complex delivery as a hands-on technical authority and mentoring others through your work.
Recent hands-on experience (2+ years) building and shipping LLM-based and agentic systems to production as part of a delivery team, using RAG, prompt engineering and agent frameworks / orchestration (e.g. LangGraph, Semantic Kernel), including evaluation, guardrails and cost management.
Expert, hands-on use of AI coding assistants and agentic development tools (e.g. Claude Code, GitHub Copilot, Cursor) to deliver exceptional personal output, with the discipline to critically review, validate and secure what they produce.
Strong engineering capability in Python and at least one of C# / .NET or TypeScript (Angular and/or React), with hands-on commercial experience of cloud (Azure preferred), GitHub or Azure DevOps, and the SDLC, CI/CD and Agile delivery.
A strong analytical and quantitative background (e.g. mathematics, statistics, engineering or computer science), with the ability to reason rigorously about data, models and uncertainty.
Strong domain knowledge of insurance, reinsurance or risk analytics (ideally actuarial or catastrophe modelling), or a record of becoming expert quickly in a complex quantitative field.
Proven ability to work directly with business users or clients and move a concept from conversation to working demo in days, then carry it into production, challenging established approaches constructively and communicating complex trade-offs clearly to senior stakeholders, actuaries and engineers alike.
Proven ability to work well both individually and as part of a team: self-directed and highly productive on your own, and collaborative in how you deliver with others, through shared backlogs, code review and handover to service teams.
Evidence of staying current at the frontier of AI: recent tools, models and techniques you have tested hands-on, and what you concluded about them.

Desirable:

Experience designing multi-agent workflows and building reusable MCP servers or tools that expose enterprise data and calculations to AI agents.
Experience running AI / LLM solutions at scale in a regulated environment, including evaluation frameworks, model governance and responsible-AI practices.
Experience with our platform stack (C# / .NET, Angular or React, Azure), microservice architectures and containerisation.
Experience with geospatial, catastrophe or financial-modelling data, or with building mathematical algorithms.
Earlier applied machine learning, statistics or data science experience, alongside your recent work with LLMs.
Visible contribution to the AI engineering community, such as open-source work, writing or speaking.
Degree-level qualification in a quantitative discipline (Mathematics, Science, Engineering or Computer Science); postgraduate study valued.
The role offers hybrid working with travel to office expected on a regular cadence for meetings and workshops.
Some occasional travel may be required as part of the engagement with business and technology stakeholders.

Note: Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity. This position will remain posted for a minimum of three business days from the date posted or until sufficient/appropriate candidate slate has been identified.

Compensation and Benefits (US locations) Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only).

Compensation

The base salary compensation range being offered for this role is $100,000– $350,000 USD per year. This role is also eligible for an annual short-term incentive bonus. Company Benefits WTW provides a competitive benefit package which includes the following (eligibility requirements apply):

Health and Welfare Benefits: Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program)
Leave Benefits: Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off
Retirement Benefits: Contributory Pension Plan and Savings Plan (401k). All Level 38 and more senior roles may also be eligible for non-qualified Deferred Compensation and Deferred Savings Plans.

Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records. EOE, including disability/vets

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More about this job

Skills

CI/CD
Cost management
Regulatory compliance
GitHub
Coaching
Python
C#
.NET
TypeScript
React
Microsoft Azure
DevOps
Agile
Statistics
Computer science
Financial modelling
Machine learning

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