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About This Role
If you are a technology visionary with a passion for transforming global tax business with digital technology, consider working with the US Tax Transformation technology team. This is an exciting opportunity to support global execution of Deloitte's tax strategy as we shift from "doing digital" to "being digital" by reimagining how we engage with our clients, deliver our services, operate our business, and create value.
Recruiting for this role ends on May 31, 2027\.
What You'll Do
As a Deloitte Tax AI Full Stack Engineer, Manager, you'll play a lead role in designing, developing, and deploying cutting\-edge web applications and features that solve key business challenges. You'll work hands\-on across the entire technology stack, collaborating closely with other engineers, data scientists, and business stakeholders to deliver robust, scalable solutions and integrate AI components into modern web applications.
Responsibilities:
- Participate in requirements analysis and collaborate on software design and architecture with US colleagues, vendors, and global team members.
- Write clean, scalable, and maintainable code using .NET programming languages; revise, refactor, and debug as needed.
- Develop, support, and maintain technology solutions, ensuring applications meet client expectations in scope, functionality, quality, and delivery standards.
- Test, deploy, and monitor applications, striving for high code quality and minimal bugs in production.
- Leverage industry best practices in software development, version control, and Agile methodologies; participate in daily SCRUM calls and provide task updates.
- Work collaboratively across on\-shore and off\-shore teams to foster a culture of teamwork and knowledge sharing.
- Continuously learn and apply project management processes, development tools, and testing methodologies relevant to the team and projects.
- Design and implement AI\-driven features in enterprise web solutions (e.g., LLM\-powered recommendations, intelligent search).
- Collaborate with data science teams to integrate and productionize machine learning models.
- Develop and optimize RESTful APIs for AI/ML services, including prompt engineering for GenAI solutions.
- Utilize Azure AI/ML platform, vector databases, and related tools for the deployment and monitoring of AI features.
The Team
Deloitte Tax LLP's Tax Transformation Office (TTO) is responsible for the design, development, and deployment of innovative, enterprise technology, tools, and standard processes to support the delivery of tax services. The TTO team focuses on enhancing Deloitte Tax LLP's ability to deliver comprehensive, value\-added, and efficient tax services to our clients. It is a dynamic team with professionals of varying backgrounds from tax technical, technology development, change management, Six Sigma, and project management. The team consults and executes on a wide range of initiatives involving process and tool development and implementation including training development, engagement management, tool design, and implementation.
Qualifications
Required:
- Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co\-locate in person 2 \- 3 days per week.
- Bachelor's degree in computer science or a relevant discipline.
- 5 \+ years of experience in full stack web development and strong hands\-on experience on C\#, SQL Server, OOPS Concepts, Micro Services Architecture.
- Demonstrated proficiency in modern front\-end frameworks (e.g., Angular, React).
- Proven hands\-on experience on .NET Core, ASP.NET Core Web API, SQL, NoSQL, Entity Framework 6 or above, Azure, Database performance tuning, Applying Design Patterns, Agile.
- Ability to travel up to 10%, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
- One of the following active accreditations obtained:
- + Licensed CPA in state of practice/primary office if eligible to sit for the CPA
+ If not CPA eligible:
+ - Licensed Attorney
- Enrolled Agent
- Technology Certifications:
- * AWS Certified Solutions Architect
- Certified SAFe® Advanced Scrum Master
- Certified SAFe® Agile Software Engineer
- Certified SAFe® Agilist
- Certified SAFe® Architect
- Certified SAFe® DevOps Practitioner
- Certified SAFe® Practitioner
- Certified SAFe® Scrum Master
- Certified Scrum Developer (CSD)
- MCSD: Application Lifecycle Management Solutions Developer
- MCSD: Web Applications
- Microsoft Azure
- Microsoft Certified Solutions Developer (MCSD)
- Microsoft Certified Solutions Expert (MCSE)
- Microsoft MCSD Certification
- Professional Scrum Developer™ (PSD)
- Professional Scrum Product Owner™(PSCPO) \- SCRUM.org
Preferred:
- Practical experience integrating and utilizing AI/ML features in web applications, including prompt engineering and working with Gen AI models.
- Familiarity with designing and integrating databases (SQL, NoSQL) and working with vector databases, RAG, and hybrid search approaches.
- Prior experience developing agentic AI applications or GenAI\-powered modules.
- Experience with Azure (cloud hosting, DevOps/build/release pipelines), MongoDB, and Entity Framework.
- Excellent troubleshooting and communication skills.
- Strong verbal and written communication skills; strong listening, interpersonal, and facilitation skills.
- Knowledge on Angular, Mongo DB, NPM and Azure Devops Build/Release configuration.
- Self\-starter with solid analytical and problem\-solving skills.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,025 to $261,625\.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Salary Context
This $128K-$261K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 219 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Deloitte, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 797 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($194K) sits 16% below the category median. Disclosed range: $128K to $261K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Deloitte AI Hiring
Deloitte has 77 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist, AI Software Engineer, Research Engineer. Positions span Stamford, CT, US, Austin, TX, US, Jersey City, NJ, US. Compensation range: $121K - $372K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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