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About This Role
The Opportunity:
As an experience d sof tware engineer, you know how to design, develop , and deliver production AI applications that demonstrate the practical value of generative AI, large language models ( LLMs ) , and autonomous workflows. You combine strong sof tware engineering fundamentals with modern AI develop ment practices to build reliable, scalable, and secure systems that solve real\-world problems.
In this role, you'll design AI applications that leverage prompting, retrieval\-augmented generation ( RAG ) , agentic workflows, evaluation pipelines, and human\-in\-the\-loop interactions to deliver measurable mission impact. You'll build modular, reusable AI capabilities that integrate multiple model providers and external tools while optimizing for performance, cost, observability, and safety.
You'll rapidly prototype and iterate using AI\-assisted develop ment tools, applying eval\-driven develop ment and continuous experimentation to validate solutions before deploying them into production.
Working alongside data engineers, data scientists, solution architects, and product owners, you'll help define the architecture and engineering practices behind mission\-critical AI applications while collaborating with a multidisciplinary team to deliver impactful mission solutions.
What You’ll Do:
- Design and develop production AI applications that integrate foundation models, retrieval systems, external tools, and enterprise data sources.
- Architect modular and reusable AI components for prompting, retrieval, orchestration, tool execution, memory, and evaluation.
- Build AI applications that leverage structured outputs, embeddings, RAG, long\-context reasoning, and agentic workflows where appropriate.
- Develop data pipelines for ingesting, transforming, indexing, and refreshing structured and unstructured data used by AI applications.
- Implement evaluation frameworks to measure correctness, robustness, safety, and mission outcomes using both automated and human evaluation techniques.
- Optimize AI applications for latency, reliability, scalability, and operational cost through experimentation, benchmarking, and continuous improvement.
- Apply asynchronous programming and event\-driven design patterns to support long\-running workflows and distributed AI applications.
- Incorporate observability, monitoring, guardrails, access controls, and responsible AI practices throughout the application lifecycle.
- Deploy AI services securely on AWS or equivalent cloud platforms using Docker, Kubernetes, serverless, or other cloud\-native deployment patterns.
- Apply modern sof tware engineering practices, including automated testing, CI / CD, prompt and workflow versioning, and safe rollout of AI updates.
- Leverage AI\-assisted develop ment tools to accelerate implementation while maintaining engineering rigor, maintainability, and code quality.
- Collaborate with clients and cross\-functional teams to identify high\-value AI opportunities, rapidly prototype solutions, and transition successful concepts into production.
- Present technical solutions to both technical and non\-technical stakeholders.
Join us. The world can’t wait.
You Have:
- 3\+ years of experience with sof tware engineering in a professional work environment
- 2\+ years of experience develop ing AI or machine learning solutions in a professional environment
- Experience building production AI applications using programming languages such as Python
- Experience designing and implementing generative AI applications using large language models
- Experience building retrieval\-augmented generation ( RAG ) solutions and integrating AI systems with enterprise data
- Experience with AI orchestration frameworks such as LangChain
- Experience develop ing AI applications that interact with external tools, APIs, or enterprise systems, and evaluating and improving AI application quality through testing, experimentation, or benchmarking
- Experience deploying cloud\-native applications using cloud platforms such as AWS
- Secret clearance
- Bachelor's degree in Computer Science, Engineering, or a technology field
Nice If You Have:
- Experience building AI applications that incorporate autonomous or agentic workflows
- Experience with multimodal AI applications involving text, images, audio, or documents
- Experience designing AI evaluation, observability, or safety frameworks
- Experience deploying portable, edge, or offline\-capable AI applications
- Experience develop ing user interfaces that enable effective interaction with AI applications
- Experience delivering technical solutions in client\-facing environments
- Experience using AI\-assisted sof tware develop ment tools to improve engineering productivity
- Master's degree in Computer Science, AI, or a related technical field
Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information ; Secret clearance is required.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well\-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work\-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full\-time and part\-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract\-specific affordability and organizational requirements. The projected compensation range for this position is $86,900\.00 to $198,000\.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in\-person or virtual) is prohibited unless permission is explicitly provided .
Work Model
Our people\-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.
- Remote : If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
- Hybrid : If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
- Onsite : If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.
Commitment to Non\-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
Salary Context
This $86K-$198K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Booz Allen Hamilton, 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 $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($142K) sits 35% below the category median. Disclosed range: $86K to $198K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Booz Allen Hamilton AI Hiring
Booz Allen Hamilton has 17 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer, AI Software Engineer, Research Engineer. Positions span Springfield, VA, US, Huntsville, AL, US, Arlington, VA, US. Compensation range: $158K - $292K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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