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About This Role
Senior AI Platform Engineer / Full Stack Software Engineer
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Location: Annapolis Junction, MD
Clearance: TS/SCI with Polygraph required
Work Type: On\-site
Salary: $190,000\-$198,000
Position Overview
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We are seeking an experienced Senior AI Platform Engineer / Full Stack Software Engineer to support the development, deployment, and operation of enterprise AI infrastructure and services. This role will help design and maintain the foundational platform that enables artificial intelligence and machine learning capabilities across the organization.
The successful candidate will work on scalable AI services, cloud\-native infrastructure, and modern software platforms while supporting the integration of emerging AI technologies into production environments. This position requires strong software engineering, cloud engineering, and platform operations expertise, along with the ability to operate effectively in dynamic and evolving technical environments.
Key Responsibilities
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- Design, implement, and optimize infrastructure supporting large\-scale AI model inference and deployment.
- Develop, maintain, and support production AI services and applications.
- Collaborate with stakeholders and engineering teams to define solutions for evolving technical requirements.
- Design and implement scalable, reliable, and maintainable platform components.
- Drive adoption of modern engineering practices, technologies, and automation solutions.
- Implement monitoring, logging, alerting, and observability capabilities for platform services.
- Automate infrastructure provisioning and configuration using Infrastructure\-as\-Code (IaC) methodologies.
- Ensure high availability, reliability, scalability, and performance of platform services.
- Support the integration of AI and machine learning capabilities into enterprise applications.
- Contribute to security, compliance, and data protection practices for cloud and AI systems.
- Provide technical guidance and mentorship to junior engineers.
- Participate in system architecture reviews, deployment planning, and operational support activities.
Required Qualifications
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### Education and Experience
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, Computer Engineering, or a related technical discipline and eight (8\) years of relevant experience; OR
- Four (4\) additional years of directly related experience may be substituted for the degree requirement.
### Technical Qualifications
- Demonstrated experience designing, building, and operating production systems at enterprise scale.
- Experience developing and supporting high\-volume web applications and distributed systems.
- Strong understanding of systems integration across diverse technologies, platforms, and services.
- Hands\-on experience designing, deploying, and managing cloud\-based solutions in Amazon Web Services (AWS).
- Experience administering and deploying applications in Kubernetes environments.
- Strong Python programming and software development skills.
- Experience implementing observability and monitoring solutions, including technologies such as:
+ OpenTelemetry
+ Grafana
+ Prometheus
+ Application Performance Monitoring (APM) platforms
- Experience with Continuous Integration and Continuous Deployment (CI/CD) pipelines.
- Knowledge of DevOps principles, automation practices, and modern software delivery methodologies.
- Ability to lead technical initiatives and influence engineering practices across teams.
- Strong communication, collaboration, and stakeholder engagement skills.
- Ability to operate effectively in environments with evolving requirements and emerging technologies.
Preferred Qualifications
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- Experience supporting AI model serving and inference platforms.
- Experience integrating large language models (LLMs) or generative AI capabilities into enterprise applications.
- Experience with AI orchestration and workflow frameworks, including LangChain or similar technologies.
- Knowledge of vector databases, embeddings, and semantic search technologies.
- Experience with Retrieval\-Augmented Generation (RAG) architectures.
- Experience with distributed computing, high\-performance computing, or large\-scale data processing systems.
- Familiarity with autonomous agent frameworks and emerging AI technologies.
Knowledge, Skills, and Abilities
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- Strong software architecture and platform engineering skills.
- Deep understanding of cloud\-native application design and operations.
- Ability to balance reliability, performance, security, and scalability requirements.
- Strong analytical and problem\-solving abilities.
- Excellent written and verbal communication skills.
- Ability to mentor and support technical team members.
- Strong organizational skills and attention to detail.
- Ability to drive technical innovation while maintaining operational excellence.
Benefits
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This position includes a competitive and flexible benefits package, including:
- Medical
Employer pays 100% of the monthly premium for the employee and 80% for the employee’s dependents.
- Health Savings Account (HSA)
Save for all medical, dental, vision and prescription expenses by contributing pre\-tax money to an HSA account. Employer contributes 50% of the annual deductible (prorated to start date).
- Dental and Vision
Employer pays 100% of the monthly premium for the employee and 80% for dependents.
- Life Insurance
100% company\-paid Life and Accidental Death \& Dismemberment (AD\&D) coverage offered to all full\-time employees.
- Short\-Term Disability
100% company\-paid short\-term disability. This benefit pays out 60% of earnings, with a $1,500 maximum for up to 12 weeks.
- Retirement Plan
Automatic 6% of salary contributed to the company 401(k) plan, fully vested. Employee match encouraged but not required.
- Paid Time Off (PTO) \& Holidays
5–6 weeks of PTO based on tenure with the company, in addition to 11 paid holidays.
- Tuition Reimbursement
$5,000 annually for courses directly related to job role and responsibilities.
- Training Reimbursement
Paid training, certification courses, and conferences to support employee career growth.
We do not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non\-merit factor.
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Salary Context
This $190K-$198K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 251 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 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At Staffed4U, 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 863 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($194K) sits 16% below the category median. Disclosed range: $190K to $198K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Staffed4U AI Hiring
Staffed4U has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Based in Annapolis Junction, MD, US. Compensation range: $198K - $306K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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