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About This Role
Opportunity ID
9594
Department
Practice Management
Location(s)
Austin
State
Texas
Function
GenAI
Job Description
As CohnReznick grows, so do our career opportunities. As one of the nation’s top professional services firms, CohnReznick creates rewarding careers in advisory, assurance, and tax with team members who value innovation and collaboration in everything they do!
CohnReznick helps organizations optimize performance, manage risk, and maximize value through CohnReznick LLP (assurance services) and CohnReznick Advisory LLC (advisory and tax services). Together, the firm provides leaders with deep industry knowledge and relationships, solutions to address clients’ unique business goals and risks, and insight on how emerging market forces can drive opportunity. With offices nationwide, the firm serves organizations around the world as an independent member of Nexia.
We currently have an exciting career opportunity for an AI Solution Software Engineer (Staff/Principal) to join our Strategic AI team.
CohnReznick is a hybrid firm and most of our professionals are located within a commutable distance to one of our offices. This position is considered remote which means it does not require job duties be performed within proximity of a CohnReznick office location. However, as a remote employee, you may be required to be present at a CohnReznick office with scheduled notice for client work, team meetings, or trainings
YOUR TEAM.
Strategic AI is a newly formed team under the COO’s organization, focused on delivering high\-impact, AI\-enhanced solutions across the firm. We are an AI\-native team, meaning that everything we do—from planning and ideation to execution—leverages AI tools by default. Our mission is to solve complex business problems through applied AI, integrating capabilities into workflows, applications, and business processes.
What We Mean by AI\-Native:
An AI\-native individual instinctively uses AI tools to plan, ideate, research, and execute tasks. AI is not an add\-on—it’s the default. This mindset includes:
- Starting every initiative with AI in mind
- Continuously learning and experimenting with the latest AI tools, models, and capabilities
- Treating AI as a core collaborator in problem\-solving and execution
WHY COHNREZNICK?
At CohnReznick, we’re united by a common mission to create opportunity, value, and trust for our clients, our people, and our communities. Whether it’s working alongside your peers to solve a client challenge, or volunteering together at the local food bank, there are so many ways to find your “why” at the firm.
We believe it’s important to balance work with everyday life – and make time for enjoyment and fun. We invest in a robust Total Rewards package that includes everything from generous PTO, a flexible work environment, expanded parental leave, extensive learning \& development, and even paid time off for employees to volunteer.
YOUR ROLE.
*Responsibilities include but not limited to:*
- Architect and develop AI\-enabled applications leveraging LLMs, ML models, GenAI, RAG/GraphRAG, and NLP/NLM techniques
- Build and maintain full\-stack web applications, ensuring production readiness: Secure, scalable, and resilient solutions, in conjunction with cyber security, risk, and IAM teams
- Design, implement secure and managed data connectors and integrations for AI use
- Document architecture, workflows, and practices; contribute to internal learning and knowledge sharing
YOUR EXPERIENCE.
*The successful candidate will have:*
- 10\+ years in software engineering, with at least 5 years in applied AI solution delivery
- Experience with Azure AI platform (OpenAI, AI Studio/Foundry, Cognitive Search), Azure Functions, and one of the coding harnesses (Claude, Copilot, Codex, Windsurf, or others)
- Strong proficiency in Python, TypeScript, and C\#; experience with full\-stack frameworks and HTTP\-based API middleware
- Expertise with GitHub, VS Code, and CI/CD pipelines
- Deep understanding of enterprise data security, governance, and compliance
- Foundational knowledge of LLM AI models, MCP, and RAG
- Demonstrated self\-learning and continuous upskilling in AI tools, models, and capabilities
- Bachelor’s or Master’s degree in Computer Science or related field (or equivalent experience)
Preferred Qualifications
- Experience in knowledge\-engineering and working with domain experts to build software that transforms and legacy processes
- Experience with written specifications and/or product management
- Experience working in high\-compliance, legally\-regulated environments such as healthcare or finance (“FinTech”)
- Familiarity with security processes and requirements
- Experience leading a team, working with outsourced engineers, providing feedback to stakeholders, and influencing technical and product roadmaps
- Experience with Dataverse, Fabric, and other similar technologies
In addition, please take a moment to review ourUniversal Job Standards.
Studies have shown that we are less likely to apply to jobs unless we meet every single qualification. At CohnReznick, we are dedicated to building a diverse, equitable, and inclusive workplace, so if you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we still encourage you to apply. You may be just the right candidate for this or one of our other roles.
"CohnReznick" is the brand name under which CohnReznick LLP and CohnReznick Advisory LLC and their respective subsidiaries provide professional services. CohnReznick LLP and CohnReznick Advisory LLC (and their respective subsidiaries) practice in an alternative practice structure in accordance with the AICPA Code of Professional Conduct and applicable law, regulations, and professional standards. CohnReznick LLP is a licensed CPA firm that provides attest services to its clients. CohnReznick Advisory LLC provides tax and business consulting services to its clients. CohnReznick Advisory LLC and its subsidiaries are not licensed CPA firms.
CohnReznick is an equal opportunity employer, committed to a diverse and inclusive team to drive business results and create a better future every day for our team members, clients, partners, and communities. We believe a diverse workforce allows us to match our growth ambitions and drive inclusion across the business. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability. For more information, please see Equal Employment Opportunity Posters
If you are an individual with a disability in need of assistance at any time during our recruitment process, please contact us at [email protected] Please note: This email address is reserved for individuals with disabilities in need of assistance and are not a means of inquiry about positions or application statuses.
CohnReznick does not accept unsolicited resumes from third\-party recruiters unless such recruiters are currently engaged by CohnReznick Talent Acquisition Team by way of a written agreement to provide candidates for a specified opening. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that CohnReznick will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.
\#LI\-CM1 \#LI\-Remote \#GD \#IND123
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 CohnReznick, 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. Senior-level AI roles across all categories have a median of $227,400.
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.
CohnReznick AI Hiring
CohnReznick has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Based in Austin, TX, US.
Location Context
AI roles in Austin pay a median of $215,300 across 523 tracked positions. That's 8% above the national 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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