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About This Role
\*\*\*REQUIREMENT: Active TS/SCI Clearance with Full Scope Polygraph\*\*\*
Are you tired of being underpaid or stuck on work that doesn’t matter?
At Shawky Engineering, we build AI solutions that directly support real\-world operational needs on the most mission essential contract in CNO. Our work is fast\-paced, high\-impact, and delivered by a small, elite team.
We operate with a lean infrastructure—no unnecessary layers, no red tape. That means:
- Above\-market compensation tied to performance.
- Minimal meetings, maximum time spent building.
- Your work ships fast and matters immediately.
We intentionally stay small to preserve agility and ensure every team member is highly valued and highly compensated.
What You’ll Do
- We are seeking an advanced modern software developer to provide rapid tactical AI solutions to CNO analysts and operators. The candidate will have several opportunities: front end UI focus, full stack, and AI agent platform.
- You will be expected to utilize AI to bridge any knowledge gaps and increase software development velocity.
- This is an AMAZING OPPORTUNITY to create tools that are used by CNO operators and analysts to reduce friction in achieving their mission goals. The candidate will work closely with analysts, operators, and other team members to create and maintain UI tools that help address important mission issues.
- This is a broad fast paced environment with the goal of having a quick turnaround to provide as much benefit to the mission as possible.
- Responsibilities: Develop frontend UIs to display user data in intuitive ways.
- Communicate directly with users to gather and integrate feedback into software solutions.
- Understand the customers mission.
- Collaborate often with team members and across other teams.
- Automate workflows
- Desire to solve problems even if you have minimal to no knowledge about how at the start.
- Skills Requirements: Java Script/Typescript and HTML/CSS experience.
- Experience developing with UI frameworks (React, Angular, etc).
- Familiarity with Relational Databases (Postgres, SQLite, MySQL etc.).
- Knowledge of basic Docker Containerization.
- Experience using Git for version control.
- Familiarity with Linux Commandline.
- Nice to Haves: CNO Experience
- Experience with Non Relational Databases (Elasticsearch, Mongodb).
- Other programing language knowledge (Java, Python, Bash, Powershell).
- Other frontend or backend frameworks (Vue, FastApi, Spring Boot etc.).
- Data science and machine learning experience.
- Experience with DevOps (GitlabCI, CI/CD, k8s, ansible).
- Any AWS or other cloud provider certification.
- YOE Requirement: 3 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.
What We’re Looking For
- Deep technical expertise across AI/ML, Python software engineering, Linux systems, and CNO, with experience leveraging modern AI development tools such as Claude Code.
- Expertise in architecting scalable, high\-impact solutions.
- Strong ability to rapidly diagnose and resolve complex issues in production environments.
- Seasoned customer service chops: engaging high level stakeholders, translating requirements, and prototying and demoing MVP capabilities.
Why Shawky Engineering
We don’t manufacture culture. It’s built by solving hard problems and delivering mission wins—together.
If you want to do your life’s work—and be paid what you’re worth—reach out to us today at [email protected]
Benefits:
- Above Market Compensation
- 10% 401k retirement gift IMMEDIATELY vested every paycheck
- 6 Weeks PTO a year! Enjoy your life!
- Excellent medical plans for you and your family including HSA
- 100% company paid dental benefits
- 100% company paid vision benefits
- 100% company paid term life insurance
- 100% company paid short\-term disability
- 100% company paid long\-term disability
- 100% company paid AD\&D Insurance
- 100% company paid training based on approval
- GUARANTEED Annual performance review to increase your pay
- MISSION ESSENTIAL contract (you won’t be sitting home unpaid during the next furlough)
Requirements:
- Active TS/SCI Clearance with Full Scope Polygraph
Pay: $185,000\.00 per year
Work Location: In person
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 Shawky Engineering, 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. Mid-level AI roles across all categories have a median of $200,000.
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.
Shawky Engineering AI Hiring
Shawky Engineering has 3 open AI roles right now. They're hiring across AI Software Engineer. Positions span Annapolis Junction, MD, US, Laurel, MD, US.
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.
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