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About This Role
##### About Peraton
Peraton is a next\-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit peraton.com to learn how we’re keeping people around the world safe and secure.
##### About The Role
Are you passionate about building cutting\-edge cloud solutions that support national security? Do you thrive in fast\-paced, mission\-driven environments? Peraton is seeking a talented and skilled Cloud Software Engineer to join our Cyber Intelligence team in Laurel, MD.
As part of a collaborative, high\-impact integrated product development team, you’ll work on next\-generation cyber and AI/ML capabilities hosted on large\-scale compute clusters and AWS Cloud infrastructure. This is your chance to help shape innovative services that make a real difference. Interested in Artificial Intelligence and Machine Learning? If so, this is the position for you.
The Cloud Software Engineer Level 2 Engineer provides cloud software research, development, and engineering services to include requirements analysis, software development, installation, integration, evaluation, enhancement, sustainment, testing, validation, and issue diagnosis/resolution.
Key Technologies and Skills:
- Cloud Expertise: Deep experience in AWS Cloud Architecture, SDKs, APIs, and cloud services integration
- AI/ML Integration: Familiarity with Large Language Models (LLMs) and Retrieval\-Augmented Generation (RAG) frameworks
- IaC \& DevOps: Hands\-on with CloudFormation or Terraform, and modern CI/CD pipelines
- Programming Proficiency: Strong in Java for distributed systems with a solid grasp of networking, multi\-threading, and concurrency
- Containers \& Orchestration: Knowledge of Kubernetes and microservices architecture
- Security\-Minded: Working knowledge of cloud security principles and compliance best practices
- Scripting \& Systems: Competent in Linux environments with scripting skills in Python, Ruby, Perl, or similar
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Python, Java, C, C\+\+, Hbase, Accumulo, Big Table, Map Reduce programming model and technologies such as Hadoop, Hive, Pig, etc., Hadoop Distributed File System (HDFS), JSON and/or BSON. Taxonomy, Ontologies, and Big\-Data Cloud Scalability (Amazon, Google, Facebook), cluster monitoring tools (e.g. Hobbit, Ganglia), Artificial Intelligence (AI), Large Language Model (LLM), Machine Learning (ML), AI/ML algorithms, statistical analysis, RAG, agents, and agentic workflow
##### Qualifications
Basic Qualifications:
- A Bachelor's Degree in Computer Science or in a related technical field is highly desired which will be considered equivalent to two (2\) years of experience.
- Five (5\) or more years of directly related experience in software development/engineering; including requirements analysis, software development, installation, integration, evaluation, enhancement, maintenance, testing, and problem diagnosis/resolution
- Must have, or be willing to obtain prior to start, one of the following Cloud Developer Certifications:
+ AWS Certified Developer\-Associate
+ AWS Certified Machine Learning\-Associate
+ AWS Certified Machine Learning\-Specialty
+ AWS DevOps Engineer Professional
+ Certified Kubernetes Application Developer (CKAD)
- A minimum of five (5\) years of experience in software development/engineering, including requirements analysis, software development, installation, integration, evaluation, enhancement, maintenance, testing, and problem diagnosis/resolution.
- A minimum of four (4\) years of experience developing software with high level languages such as Java, C, C\+\+
- Demonstrated ability to work with OpenSource (NoSQL) products that support highly distributed, massively parallel computation needs such as Hbase, Acumulo, Big Table, etc.
- Demonstrated work experience with the Map Reduce programming model and technologies such as Hadoop, Hive, Pig, etc.
- Demonstrated work experience with the Hadoop Distributed File System (HDFS)
- Demonstrated work experience with Serialization such as JSON and/or BSON
- Demonstrated work experience developing Restful services
- At least three (3\) years of experience developing software for UNIX/Linux (Redhat versions 3\-5\) operating systems.
- Demonstrated work experience in the requirements analysis and design of at least one Object Oriented system.
- Demonstrated work experience developing solutions integrating and extending FOSS/COTS products.
- At least three (3\) years of experience in software integration and software testing, to include developing and implementing test plans and test scripts.
- Demonstrated technical writing skills and shall have generated technical documents in support of a software development project.
In addition, the candidate will have demonstrated experience, work or college level courses, in at least two (2\) of the desired characteristics:
- Experience deploying applications in a cloud environment.
- Understanding of Big\-Data Cloud Scalability (Amazon, Google, Facebook)
- Experience designing and developing automated analytic software, techniques, and algorithms.
- Experience with taxonomy construction for analytic disciplines, knowledge areas and skills.
- Experience developing and deploying: data driven analytics; event driven analytics; sets of analytics orchestrated through rules engines.
- Experience with linguistics (grammar, morphology, concepts).
- Experience developing and deploying analytics that discover and exploit social networks.
- Experience documenting ontologies, data models, schemas, formats, data element dictionaries, software application program interfaces and other technical specifications.
- Experience developing and deploying analytics within a heterogeneous schema environment.
An Active TS/SCI clearance with polygraph is required
Desired Qualifications:
- Experience with Large Language Models (LLM), Agentic AI, and Retrieval\-Augmented Generation (RAG)
- Expertise in AWS Cloud Architecture design and development
- Proficiency in using AWS SDKs and APIs
- Expertise in Infrastructure as Code (IaC) tools like CloudFormation or Terraform
- Skilled in Continuous Integration, Deployment, Testing and Monitoring practices
- Knowledge and skill in implementing and using observability tools (e.g. Elasticsearch, OpenSearch)
- Java programming for distributed systems, with experience in networking and multi\-threading
- Agile development experience with source code management practices and tools
- Well\-grounded in Linux fundamentals and knowledge in at least one scripting language (e.g. Python, Ruby, Perl, etc.)
- Familiarity with microservices software development techniques and container\-orchestration (e.g., Kubernetes)
- Knowledge of security and compliance best practices
Benefits: *Peraton offers enhanced benefits to employees supporting this critical National Security program, which include heavily subsidized employee benefits coverage for you and your dependents, 25 days of PTO accrued annually up to a generous PTO cap, and eligibility to participate in an attractive bonus plan.*
Investing in Your Growth: *Selected candidates may be eligible for enhanced professional development opportunities, including training, certification programs, and skill\-building experiences tailored to individual strengths, career goals, and role\-specific requirements.*
##### Details
Target Salary Range: $146,000 \- $234,000\. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Benefits Statement: Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.
Application Statements: The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. By applying to this job, you are expressing interest in the role and the Company. During the review of your application, you may be required to participate in an on\-camera interview, as well as participate in a process to verify your identity.
EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.
Salary Context
This $146K-$234K range is above the median for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Peraton, 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 $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($190K) sits 13% below the category median. Disclosed range: $146K to $234K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Peraton AI Hiring
Peraton has 10 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer, AI Software Engineer. Positions span Red Bank, NJ, US, Herndon, VA, US, Basking Ridge, NJ, US. Compensation range: $166K - $304K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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.
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