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About This Role
Grow, innovate, and generate progress: Harness your expertise to solve challenges and celebrate success!
Job Summary
JCS Solutions is seeking an experienced AI and Automation Solutions Engineer to support the NICHD program in Bethesda, Maryland. You will design, develop, deploy, and support enterprise automation, endpoint-management solutions, AI-assisted tools, and low-code applications that enhance IT operations, reporting capabilities, and service delivery. The ideal candidate combines strong endpoint management and PowerShell automation expertise with practical experience developing AI-enabled and Microsoft Power Platform solutions in a secure, enterprise environment.
Location: Bethesda, MD
Clearance: Ability to obtain or hold a Public Trust Tier II
Salary: $100,000.00 - $135,000.00
What’s in it for you:* Join a premier technology firm specializing in innovative solutions.
- Be part of a collaborative, inclusive, and innovative work culture.
- Enjoy tremendous growth potential in a high-performing team environment.
- A robust benefits package: + Health, dental, and vision insurance + Life insurance + Short-and-long term disability + Paid time off (PTO) + 401k retirement plan with employer match + Annual Professional Development Reimbursement Program + And more!
What you will do:* Develop, test, deploy, and support PowerShell automation solutions for enterprise IT operations.
- Design and maintain SCCM-based software deployments, configuration baselines, reporting solutions, and remediation workflows.
- Build approved AI-assisted solutions, including agents, GPTs, plugins, skills, prompts, connectors, and MCP-based integrations.
- Create low-code applications, workflows, portals, dashboards, reports, and AI-enabled capabilities using Microsoft Power Platform technologies.
- Develop solutions utilizing Power BI, Power Automate, Power Apps, Power Pages, and Copilot Studio.
- Integrate applications and automation platforms with Microsoft 365 services, endpoint-management platforms, ticketing systems, data sources, and APIs.
- Perform testing, validation, monitoring, troubleshooting, and operational support activities.
- Maintain version control, logging, documentation, change records, rollback plans, and security review artifacts.
- Ensure solutions comply with cybersecurity, privacy, accessibility, change-management, and lifecycle management requirements.
- Validate AI-generated outputs and ensure appropriate protection of sensitive information.
What you will bring:* Hands-on experience with SCCM, Intune, BigFix, or a comparable enterprise endpoint-management platform, including software distribution, patch management, configuration baselines, deployment validation, and reporting.
- Strong PowerShell scripting and automation development experience, or comparable enterprise scripting/development expertise.
- Demonstrated experience building and supporting enterprise automation solutions in production environments.
- Practical experience using approved generative AI technologies and developing agents, connectors, plugins, skills, prompts, or comparable reusable AI-enabled components.
- Hands-on development experience with Microsoft Power Platform technologies, including multiple services such as: + Power BI + Power Automate + Power Apps + Power Pages + Copilot Studio
- Experience integrating applications with enterprise platforms, APIs, and Microsoft services.
- Ability to independently test, validate, and verify AI-generated outputs prior to implementation.
- Strong documentation, troubleshooting, and operational support skills.
- Ability to work within established cybersecurity, privacy, accessibility, change-management, and solution lifecycle processes.
- Ability to obtain or maintain an HHS Public Trust Tier II background investigation.
How you will wow us:* Experience with BigFix and JAMF Pro.
- Experience administering Active Directory and Group Policy.
- Experience using Microsoft Graph, REST APIs, JSON, and Dataverse.
- Experience with source control and Power Platform Application Lifecycle Management (ALM).
- Certifications: Microsoft Power Platform, Power BI, Azure, Microsoft 365, or SCCM-aligned certification.
JCS Solutions (JCS) is a premier technology firm providing innovative solutions and high-quality services in defense, national security, and civilian sectors. JCS offers enterprise-wide solutions including cloud computing, software development, cybersecurity, digital modernization, and management consulting for the federal government. At JCS, we elevate our customers’ mission through the application of technology and professional services. Our commitment to investing in our workforce drives innovation and progress for our clients, employees, and communities.
JCS is both a Great Place to Work and a Top Places to Work certified company.
Our employees embody our core values, and we are looking for others who do too!* Customer Experience: Strive for excellence and delight our clients
- Innovation: Embrace creative thinking to enable continual growth and powerful solutions
- Accountability: Take ownership of and pride in our actions and service delivery
- Inspire: Be inspired to be your best self and have fun in the process
- Integrity: Do the right thing, the right way, every time!
- Stewardship: The careful and responsible management of something entrusted to our care.
At JCS Solutions, compensation is based on a number of factors such as location, qualifications, and applicable contract terms. The general salary range for this position is as follows: $115,000.00 to $135,000.00
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to any protected status protected by applicable federal, state, or local laws. NOTICE: Please be aware that all JCS Solutions communications related to job interviews and offers from our recruiting team will only come from @JCSSolutions.com. We want to emphasize that we do not conduct any interviews over Discord, Slack, Skype, Zoom, or any chat app.
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Salary Context
This $100K-$135K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At JCSSolutions, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($117K) sits 45% below the category median. Disclosed range: $100K to $135K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
JCSSolutions AI Hiring
JCSSolutions has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Bethesda, MD, US. Compensation range: $135K - $135K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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