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About This Role
Artificial Intelligence (AI)/Machine learning\- Software Engineer 2
Location: Annapolis Junction, MD \| Onsite Clearance Required: TS/SCI with Polygraph Employment Type: Full\-Time Salary Range: $206,600\-$229,600
Join a Growing Team at WeeghmanBriggs
WeeghmanBriggs is seeking a motivated and mission\-driven Artificial Intelligence (AI)/Machine learning\- Software Engineer 2 to support critical government initiatives in Annapolis Junction, MD.
Founded in 2016 by Anthony Jordan, WeeghmanBriggs specializes in delivering high\-impact analytical services to Government Agencies and private organizations. Since our founding, we have partnered with a range of federal entities and private corporations, earning a strong reputation as a trusted, results\-driven company with an exceptional team of professionals.
As we continue to expand across current programs and upcoming contract awards, we are looking for talented individuals who want to contribute, grow, and build something meaningful alongside us.
At WeeghmanBriggs, you're more than a number, you're part of the team. We've built a culture where your opinion matters, your voice is heard, and your contributions make a direct impact on mission success. Our growth creates opportunity for advancement, leadership visibility, and long\-term career development while maintaining the supportive, close\-knit environment that sets us apart.
If you're ready to grow your career while supporting important national missions, we'd love to connect with you.
What You'll Do
- Support mission\-critical programs in secure government environments
- Analyze requirements and translate them into actionable solutions
- Collaborate with cross\-functional teams to deliver high\-quality results
- Ensure compliance with contract and security standards
- Contribute ideas to improve processes, efficiency, and performance
- Work directly with mission users to capture workflows, document operational decision points, and translate them into effective AI enabled capabilities
- Design and implement solutions that may include LLM powered workflows, agent\-based automation, or hybrid approaches depending on mission needs
- Your work will streamline analytical tasks, improve data accessibility, and support rapid, informed decision making in high tempo environments
- Collaborate with operations, analysts, developers, and mission leadership to ensure solutions integrate cleanly with existing systems, perform reliably in production, and adhere to the security and governance expectations of classified environments
What You Bring
- Active TS/SCI with Polygraph
- Bachelor's degree and 14 years of experience with 3\+ years of experience in AI/ML engineering, data science, or software engineering within cyber, intelligence, or national security environments
- Experience supporting government or DoD programs
- Ability to work independently and within a collaborative team environment
- Strong written and verbal communication skills
- Experience capturing user workflows and translating them into structured process maps, automation requirements, or executable logic
- Experience designing or implementing LLM based or agentic workflows, including multi step reasoning, tool integrations, and orchestration
- Experience integrating AI systems with APIs, enterprise data stores, or mission platforms
- Experience with programming languages such as Python
Preferred Qualifications
- Relevant certifications (Security\+, CISSP, PMP, AWS, etc.)
- Agile, cloud, or modernization experience
- Background in process improvement or analytical services
- Experience engineering AI capabilities in on premise or multi classification environments
- Experience with AWS or Azure, including work in restricted or classified environments
- Experience with AI/LLM development framework such as LangChain, LangGraph, PydanticAI, or CrewAI
- Experience with ML frameworks such as PyTorch, TensorFlow, vLLM, or llama.cpp
- Experience with cyber or intelligence workflows, operational data types, or mission oriented analytical processes
- Master's degree in AI, ML, Data Science, Cybersecurity, or Engineering
CompensationBenefits
The projected salary range for this position is $206,600\-$229,600, dependent upon experience, qualifications, and contract requirements.
At WeeghmanBriggs, we believe our people are our greatest strength. We offer a competitive benefits package designed to support you both professionally and personally.
Learn more about our comprehensive benefits here: https://weeghmanandbriggs.com/summary\-of\-employee\-benefits/
Equal Employment Opportunity
WeeghmanBriggs is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local laws.
Salary Context
This $206K-$229K range is above the 75th percentile 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 Weeghman & Briggs, 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. Disclosed range: $206K to $229K.
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.
Weeghman & Briggs AI Hiring
Weeghman & Briggs has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Jessup, MD, US. Compensation range: $229K - $229K.
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.
Frequently Asked Questions
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