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About This Role
Position Summary
Software Engineer III\- AI \& Engineering/Software as a Service
Join our AI \& Engineering team transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re\-engineering operations and processes that are critical to business. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
AI \& Engineering leverages cutting\-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission\-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology \& data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models\-traditional teams, pools, or pods\-are tailored to each client's needs, offering engineering\-led advisory, implementation, and operational capabilities to accelerate innovation.
Recruiting for this role ends on 8/1/26
Work You'll Do
You are a hands\-on technical leader who designs, builds and ships scalable software systems while mentoring junior engineers and driving technical best practices across the organization. You will architect full\-stack and agentic AI solutions, guide distributed engineering teams, and engage with product managers, designers, and stakeholders to deliver high\-impact solutions.
A successful candidate would possess these skills:
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast\-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
Key Responsibilities
- Architect, design, and implement scalable, reliable, and maintainable full\-stack software systems and services.
- Design and operationalize RESTful and asynchronous APIs on cloud\-native infrastructure (AWS, Azure, or GCP), including containerized workloads, CI/CD pipelines, and infrastructure\-as\-code.
- Lead end\-to\-end delivery of complex features from requirements gathering through deployment and monitoring.
- Architect and deliver production\-grade agentic AI and multi\-agent applications using popular frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel; design patterns including orchestrator\-agent hierarchies, RAG pipelines, tool\-calling agents, and context/memory management.
- Conduct thorough code reviews, enforce coding standards, and champion engineering best practices.
- Mentor and guide junior and mid\-level engineers, fostering a culture of continuous learning and improvement.
- Collaborate with cross\-functional teams including Product, Design, DevOps, and QA to deliver high\-quality software.
- Identify technical debt and proactively drive refactoring and improvement initiatives.
- Participate in system design discussions, architecture reviews, and technical planning sessions.
- Troubleshoot and resolve complex performance, scalability, and reliability issues in production systems.
- Contribute to hiring processes including technical interviews and assessments.
Qualifications
- 5\+ years of relevant consulting or industry experience in a hands\-on development role, working across borders and as an integral team member.
- 5\+ years of full\-stack software development experience with proficiency in at least one back\-end language (Python, Java, .NET/C\#, Go, or Node.js) and a modern front\-end framework.
- 4\+ years building microservices and scalable APIs in a distributed, enterprise environment.
- Solid knowledge of relational and/or NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB, etc.).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes).
- Excellent problem\-solving skills with a strong ability to debug and optimize complex systems
- Proven track record managing or technically leading delivery teams, including communication cadences and quality assurance across time zones.
- Experience delivering software across multiple SDLC methodologies (Agile, SAFe, Kanban, waterfall\-agile hybrid).
- Bachelor's degree in Computer Science, Engineering, or a related discipline \- or equivalent professional experience.
- Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available
In addition, successful Software Engineer IIIs will have the following preferred background:
- Experience with event\-driven architectures and messaging systems (Kafka, RabbitMQ, SQS).
- Contributions to open\-source projects or a demonstrated personal portfolio.
- Experience with machine learning pipelines or data engineering workflows.
- Demonstrated experience designing and delivering solutions that incorporate Large Language Models (LLMs) and/or agentic AI architectures in a professional setting.
- Knowledge of security best practices, including OWASP guidelines and secure coding standards.
- Prior experience in a tech lead or staff engineer capacity.
- Industry\-recognized technology certifications.
Wages \+ Salary
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 $122,000 to $240,500
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 $122K-$240K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 193 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 3,824 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 $234,620 based on 682 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($181K) sits 23% below the category median. Disclosed range: $122K to $240K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Deloitte AI Hiring
Deloitte has 72 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer, Data Scientist, AI Software Engineer. Positions span New York, NY, US, Gilbert, AZ, US, Arlington, VA, US. Compensation range: $121K - $372K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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