AI Engineer/Forward-Deployed Engineer

Willis Towers Watson; Austin, Northern (TX, KY); Hybrid; USD 125,000 - 250,000; Full time

Benefits offered by this job

Health benefits

401k savings plan

Paid time off

Job summary

Willis Towers Watson is seeking an experienced AI Engineer / Forward Deployed Engineer to design, build, and operate production-grade AI solutions inside enterprise environments. You’ll translate business needs into AI-enabled workflows, connect systems, validate outputs, and ensure reliability, security, and adoption across teams.

This role requires deep full-stack expertise ( .NET, Azure, SQL, React/Angular ) and a track record in distributed systems, observability, and AI tooling such as LLMs

Qualifications

• Significant professional experience in software engineering, technical leadership, solutions architecture, or platform engineering.
• Proven ability to design and deliver production applications using APIs, distributed systems, microservices, automated testing, CI/CD, observability, and cloud platforms.
• Hands-on experience building AI-enabled systems, such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, or agentic workflows.
• Experience with business-critical systems where reliability, maintainability, and operational support are essential.
• Experience collaborating with data scientists, product managers, QA teams, architects, security teams, and senior stakeholders.
• Track record of mentoring engineers, leading technical delivery, and establishing engineering standards.

Responsibilities

• AI solution delivery: Design and build AI-enabled applications, copilots, agents, extraction pipelines, and decision-support tools.
• Forward deployed problem solving: Translate real workflows into working technical solutions with business teams.
• LLM and agent engineering: Build and tune LLM workflows, prompts, schema-driven extraction, and tool-calling patterns.
• Enterprise integration: Integrate AI solutions with enterprise systems, APIs, data platforms, and IAM services.
• Production engineering: Ensure reliability, scalability, latency, cost control, logging, and operations support.
• Architecture and leadership: Define solution architecture and engineering standards for AI platforms.
• Data readiness: Prepare structured/unstructured data, improve metadata, and retrieval strategies.
• Security and governance: Embed access controls, audit logging, data protection, and responsible AI practices.
• Adoption and enablement: Deliver demos, pilots, training, and feedback loops to drive value.

Skills

Software engineering

Solutions architecture

Distributed systems

AI-enabled systems

Leadership mentoring

Tools

.NET

Azure

SQL

React/Angular

LLMs

Retrieval pipelines

Job description

Description

The Role

The AI Engineer / Forward Deployed Engineer is responsible for designing, building, integrating, and operating production-grade AI solutions that solve real business problems inside complex enterprise environments. The role combines hands-on software engineering, AI solution architecture, customer or business stakeholder engagement, and end-to-end delivery ownership.

Unlike a traditional AI or software engineering role focused only on internal product backlogs, this role works close to the operational problem. The engineer translates ambiguous business needs into deployed AI-enabled workflows, connects enterprise systems and data sources, validates output quality, and ensures solutions are reliable, secure, cost-effective, and adopted by users.

This position is ideal for an experienced Solutions Architect, Staff Engineer, or Technical Lead with a strong enterprise engineering background and a passion for applying it to AI-enabled systems. You’ll bring deep expertise across modern full-stack technologies (.NET, Azure, SQL, React/Angular), along with experience in distributed systems, observability, and AI tooling such as LLMs, retrieval pipelines, and agentic workflows.

Acting as a bridge between business and technology, you’ll work across product, data science, architecture, and engineering teams—mentoring others, resolving production challenges, and scaling prototypes into robust, enterprise-grade solutions that deliver real impact.

The Responsibilities

• AI solution delivery: Design and build AI-enabled applications, copilots, agents, extraction pipelines, prediction interfaces, and decision-support tools using foundation models, retrieval-augmented generation, structured outputs, and orchestration frameworks.
• Forward deployed problem solving: Work directly with business teams, product owners, clients, or operational users to understand real workflows, constraints, data quality issues, and adoption barriers, then translate these into working technical solutions.
• LLM and agent engineering: Build and tune LLM workflows, prompt strategies, schema-driven extraction, tool-calling patterns, agent orchestration, evaluation loops, and human-in-the-loop controls.
• Enterprise integration: Integrate AI solutions with enterprise systems, APIs, data platforms, document repositories, workflow tools, observability platforms, and identity and access management services.
• Production engineering: Ensure AI solutions meet enterprise standards for reliability, scalability, latency, maintainability, cost control, logging, monitoring, and operational support.
• Evaluation and quality assurance: Create evaluation datasets, test harnesses, validation tools, regression checks, and quality review workflows to measure accuracy, extraction quality, hallucination risk, and business usefulness.
• Architecture and technical leadership: Define solution architecture, engineering standards, reusable patterns, and implementation approaches for AI-enabled platforms and services.
• Data and knowledge readiness: Work with engineering, data, and business teams to prepare structured and unstructured data, improve metadata, design retrieval strategies, and identify gaps in source content.
• Security, privacy, and governance: Embed access controls, audit logging, data protection, responsible AI controls, security review, and compliance requirements into the AI delivery lifecycle.
• Adoption and enablement: Support users through demos, pilots, training, feedback loops, documentation, and iterative improvement so that deployed AI solutions create measurable business value.

Qualifications

The Qualifications

• Significant professional experience in software engineering, technical leadership, solutions architecture, or platform engineering, ideally in enterprise-scale environments.
• Proven ability to design and deliver production applications using modern engineering practices, including APIs, distributed systems, microservices, automated testing, CI/CD, observability, and cloud platforms.
• Hands‑on experience building AI-enabled systems, such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, prediction interfaces, or agentic workflows.
• Experience working with business‑critical systems where reliability, maintainability, operational support, and measurable business impact are essential.
• Experience collaborating with data scientists, product managers, QA teams, architects, security teams, and senior stakeholders.
• Track record of mentoring engineers, leading technical delivery, establishing engineering standards, and influencing teams beyond direct line management.

This position will remain posted for a minimum of three business days from the date posted or until a sufficient/appropriate candidate slate has been identified

Compensation and Benefits

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 base 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.

Compensation

The base salary compensation range being offered for this role is $125,000-$250,000 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