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About This Role
At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations.
Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more.
Join us to drive positive, lasting change that moves missions and the government forward!
Accenture Federal Services is seeking a Full Stack Software Engineer proficient with AI-driven Software Development to join our team and support our client in San Antonio, TX.
The AI‑Enhanced Full‑Stack Engineer applies modern Java and JavaScript development skills and emerging AI‑driven engineering practices to build secure, scalable, mission‑focused applications in support of Globally Integrated Operations. This role blends traditional full‑stack software development with hands‑on use of AI tools including code‑assist technologies, automated refactoring, intelligent testing, and AI‑supported troubleshooting to accelerate delivery and elevate overall system reliability. The engineer contributes across backend, front‑end, and automation layers, helping modernize applications while integrating AI‑assisted workflows that reduce manual effort and improve performance.
What you'll be doing:
- Design, develop, and maintain scalable, mission‑driven web applications across the full technology stack
- Build and optimize backend services using Java, ensuring secure, efficient, high‑performance data processing
- Develop and integrate RESTful APIs, contributing to reliable service-to-service communication
- Create responsive, accessible, user‑focused front‑end interfaces using JavaScript and modern frameworks
- Partner closely with product managers, designers, and engineers to translate requirements into technical solutions
- Troubleshoot issues across the stack, improve system reliability, and continuously enhance performance
- Demonstrate ownership, problem‑solving abilities, and a commitment to secure, maintainable, high‑quality software delivery
What you'll need:
- Minimum 3 years of experience with:
- + Java, JavaScript, and/or front‑end frameworks such as React, Angular, or Vue.js + Ansible (hands‑on experience)
- Experience developing, building, consuming and/or securing RESTful APIs
- Experience with SQL and/or NoSQL databases (PostgreSQL, MySQL, MongoDB, Elasticsearch)
- Experience working with Node.js
- Experience leveraging code assist technologies while developing applications (e.g., Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, etc.)
Bonus Points if you have:
- Experience with Apache Spark & NiFi
- Experience integrating AI & LLM languages into legacy architecture
- Familiarity with technologies such as Accumulo, Hadoop, Zookeeper, YARN, or similar data‑ecosystem tools
- Experience with Docker, Linux, AWS, and Kubernetes
- Experience using AI‑augmented CI/CD tools that automate documentation, test generation, dependency updates, or pipeline recommendations
- Ability to apply AI‑assisted security scanning tools to identify vulnerabilities or misconfigurations
- Familiarity with AI‑supported infrastructure automation workflows (e.g., Ansible playbook generation, automated config validation)
- DoD 8140 compliance (e.g. Security+, CISSP, CASP, etc.)
Clearance:
Must have an active Top Secret level clearance; SCI preferred
What We Believe**As a company wholly dedicated to serving the US federal government, we bring together the best talent to help reinvent how federal agencies operate and deliver greater value for their mission and the American people. We have an unwavering commitment to creating a culture in which all our people are respected, feel a sense of belonging, and have equal opportunity. As a business imperative, every person at Accenture Federal Services has the responsibility to create and sustain a culture where everyone feels welcomed and included. This is grounded in our core values and our experience that hiring and developing great people who reflect different perspectives, experiences, and backgrounds is key to driving innovation and delivering the results that our clients and the country count on.
Equal Employment Opportunity Statement We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. For details, view a copy of the Accenture Federal Services Equal Opportunity Policy Statement.
Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women.
Requesting An Accommodation Accenture Federal Services is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture Federal Services and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.
If you**are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter.
Other Employment Statements Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.
California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please click here for additional important information.
Salary Context
This $103K-$196K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 198 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 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Accenture Federal Services, 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 $220,000 based on 1,601 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($149K) sits 32% below the category median. Disclosed range: $103K to $196K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Accenture Federal Services AI Hiring
Accenture Federal Services has 13 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Data Engineer. Positions span Arlington, VA, US, Arlington, VA, Columbia, MD, US. Compensation range: $170K - $269K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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