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About This Role
Job Description:
NetImpact Strategies is seeking an AI/DevSecOps Installation Architect to join our Product Team. This role serves as a senior technical leader responsible for architecting, integrating, and delivering innovative AI\-enabled solutions that accelerate digital transformation across Federal Government organizations. As a key member of the AI Forge Product Team, the Architect will define technical strategy, establish enterprise integration patterns, and guide the development of scalable solutions that leverage artificial intelligence, automation, and modern cloud technologies. This individual will collaborate with product managers, engineers, data architects, and client stakeholders to design secure, scalable, and mission\-focused solutions that enable agencies to maximize the value of AI\-powered capabilities. The Technical Architect will play a critical role in shaping the AI Forge product roadmap and ensuring seamless interoperability across complex enterprise environments. Typical Responsibilities Include:
- Lead product installations for customers
- Serve as lead for the technical team, leveraging experience and judgment to resolve issues as a point of escalation. These discussions may entail:
- + Identifying strategies to create better collaboration among developers, testers, project managers, and users, using development methods and automated practices
+ Creating/implementing innovative technical solutions within budget/timelines that prove successful (metrics/feedback) to alleviate manual workload and burden
- Define the system, technical, and application architectures for critical areas of development and recommend a course of action to maintain cost\-effectiveness and competitiveness
- Provide hands\-on support for agile development, defect/bug triage, and fixes while ensuring long\-term technical sustainability and architectural soundness:
- + Leading Sprint retrospectives
+ Supporting peer and management code reviews
- Participate in business and technical requirement sessions
- Provide technical estimates and a rough level of effort (SWAG)
- Work effectively and efficiently on tight deadlines as necessary
- Perform code reviews for functional accuracy and alignment with best practices, or develop Best Practices unique to the technology stack and customer environment
- Stay up to date on business initiatives and objectives, particularly infrastructure and development architecture issues.
- Research and implement best practices frameworks/capability models that will control costs, provide higher quality, and increase the predictability of service delivery.
- Develop Proof of Concept prototypes to demonstrate the value or benefits of new technologies and processes, e.g.:
- + Improving quality and reducing effort for development testing, including the creation of test cases and automating tests
- Provide technical inputs in an understandable format for Senior Executive briefings and other reports, including:
- + Delivering complex presentations or demos to describe functional changes or requirements released with the latest package or image
+ Team performance based on task completion, challenges, issues, and status using a centralized requirements management tool
+ State of progress against strategic roadmap, both technical and business
- Work with Functional SMEs and Developers to estimate the level of effort (LOE) of requirements and design solutions or development tasks that meet short\-term and long\-term needs using comprehensive, realistic, and effective plans
- Recognize problems or situations that are new or without clear precedent; evaluate alternatives and recommend solutions using a systematic, multi\-step approach based on LOE and impact assessments
- Regularly review and provide LOE estimation inputs to the application backlog as a part of continuous backlog grooming, support technical design discussions, and provide inputs during Sprint grooming to release features
- Support user acceptance testing and demos and participate in code reviews, as required
Qualifications:
Required Skills:* US Citizenship is required
- Bachelor’s degree in any field with at least 5 years of combined commercial and Federal experience in software development, DevOps, and technical leadership.
- Public trust eligible (preference over resources who already possesses a Public Trust and/or a DoD CAC)
- 5 years\+ of progressive experience and proficiency in the following:
+ AWS
+ Azure
+ Terraform
+ CLIs
+ Opensource Tech Stack
+ Native Cloud Services\& Serverless Technologies
- Demonstrated ability to:
+ Manage large\-scale applications supporting large user bases (1000\+ concurrent users)
+ Provide technical architecture improvement recommendations
+ Independently create successful technical solutions to address business needs of similar complexity
+ Provide review and QA for the work of others on the team and train and lead junior team members
+ Accept ultimate responsibility for the overall IT solution to business problems presented on the project, and ensure the solutions are appropriately implemented
+ Support modernization and migration of functionality and data between various systems
- Provide technical expertise throughout the Systems Development Life Cycle (SDLC) using DevOps/DevSecOps. This capability includes:
+ Software design recommendations, development plans, system modeling and analysis, product/service capability analysis, and technical documentation for custom applications
- Lead the specifications, design, development, and maintenance of large\-scale, Internet\-based applications, frameworks, and platforms.
- Research new tools and technologies and come up with recommendations on deploying them in client applications, including:
+ Maintaining and improving GitX processes and other DevOps workflows, including automation workarounds and innovations for the team in building a more robust capacity
- Strong verbal and written communications skills, particularly in translating technical concepts into an understandable format
- Self\-starting and self\-managing – the ability to work independently to complete tasks and proactive reach out to resolve challenges promptly
- Strong customer\-service attitude
Desired Skills:* Experience designing, modifying, and implementing complex software programming components and applications for application enhancements/upgrades that requires:
- + Development using NodeJS, Python
Experience with GitLab, AWS CodeCommit, GitHub
Experience with DevSecOps/DevOps deployment in CI/CD layer to web\-based cloud platforms (particularly AWS GovCloud PaaS)
Experience with Kubernetes
Experience with RHEL7 Linux
Experience with IronBank images
- Familiarity with Identity and Authentication Systems (ForgeRock) and frameworks (OIDC)
- Familiarity with no SQL databases (MongoDB)
- Troubleshoot complex application problems and defects in a custom technology build
- Drive software design for agile software teams, including patterns, design diagrams, and team direction and mentorship.
\#LI\-Remote
Salary Minimum: USD $145,000\.00 Salary Maximum: USD $175,000\.00 About Us:
*Perks of working at NetImpact Strategies*
- Your health comes first – we offer comprehensive medical, dental, \& vision insurance that starts the first of the month after you join the team
- Invest in your future – 401(k) Plan – Immediately vested employer contributions; no matching required
- Work hard, play hard – we offer a generous Paid Time Off (PTO) policy, one (1\) additional day of paid wellness leave per calendar year, and observe ten (10\) federal holidays
- Pawsitively pawesome – Pet Insurance (because our little critters are part of our families, too!)
- Invest in your education – Tuition reimbursement, internal training programs, \& company\-sponsored industry certifications!
- Be part of a dynamic and collaborative work environment recently ranked by The Washington Post as a Top Work Place in 2019, 2021,2022, 2023, \& 2024!
- Have fun and celebrate and give back – Team building activities, community volunteering, quarterly HQ days, wellness events, happy hours, family fun events, and more!
ABOUT US
NetImpact Strategies Inc. (NetImpact) has been a Trusted Advisor driving impact through digital transformation for the Federal Government for over a decade. We solve complex problems with innovation and agility to create meaningful, transformative, and enduring change. As Trusted Advisors, NetImpact professionals partner with customer agencies to deliver solutions that empower them to not only meet their missions but also realize their strategic vision through agile, outcome\-focused solutions addressing both strategic and tactical requirements. We design and implement comprehensive, tailored solutions that are both mindful of the client's culture and organizational dynamics. NetImpact’s core values and commitment to a customer and results\-oriented delivery approach has propelled our growth and enabled us to deliver impactful value across Strategic Consulting, Process Automation, Cloud, DevSecOps, Data and Analytics, and Cyber Security for the Federal Government.
ACCESSIBILITY NOTE
NetImpact Strategies is committed to complying with all applicable provisions of the Americans with Disabilities Act, as amended (“ADA”), and applicable state and local laws. It is NetImpact’s policy not to discriminate against any qualified person or applicant with regard to any terms or conditions of employment on the basis of such individual’s disability. Consistent with this policy of non\-discrimination, NetImpact will provide reasonable accommodations to an individual with a disability, as defined in the ADA or applicable law, who has made NetImpact aware of his/her disability, unless doing so would cause undue hardship to NetImpact. If you are an applicant and need reasonable accommodation when applying for job opportunities within NetImpact, or request reasonable accommodation to utilize NetImpact’s online employment application, please contact [email protected].
Salary Context
This $145K-$175K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At NetImpact Strategies Inc, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($160K) sits 27% below the category median. Disclosed range: $145K to $175K.
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.
NetImpact Strategies Inc AI Hiring
NetImpact Strategies Inc has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $175K - $175K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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 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).
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 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.
Frequently Asked Questions
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