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About This Role
Koniag Management Solutions, LLC a Koniag Government Services company, is seeking an AI/ML Engineer with a Secret security clearance to support KMS and our government customer in Huntsville, AL. This is an onsite position.
We offer competitive compensation and an extraordinary benefits package including health, dental and vision insurance, 401K with company matching, flexible spending accounts, paid holidays, three weeks paid time off, and more.
Koniag Government Services is seeking an AI/ML Software Engineer to join a small, high\-impact AI and Automation team supporting U.S. Army mission operations. In this role, you will design, develop, and deploy AI\-powered applications and automation solutions that streamline complex government workflows and improve decision\-making for military end users. You will work across the full development lifecycle, from prototyping AI/ML features to building production\-grade web applications and maintaining the CI/CD pipelines that deliver them.
This is a hands\-on engineering position suited for early\-career professionals who are eager to grow technically in a fast\-moving environment. You will work within a dedicated AI and Automation team and collaborate closely with cross\-functional teams spanning Software Development, Data Analytics, and Infrastructure, contributing meaningfully to architecture decisions, development work, and deployment operations from day one. The ideal candidate brings a strong foundation in AI/ML concepts, modern software development practices, and the adaptability to work across frontend, backend, and infrastructure as needed.
Essential Functions, Responsibilities \& Duties may include, but are not limited to:
AI/ML Development and Integration:
- Develop and integrate AI/ML capabilities into mission\-focused web applications, including large language model (LLM) integration, retrieval\-augmented generation (RAG) pipelines, and intelligent automation workflows
- Assist in the design and implementation of data ingestion, embedding, vector search, and model serving pipelines
- Support prompt engineering, model evaluation, and performance tuning for deployed AI features
- Research and prototype emerging AI/ML tools, frameworks, and techniques to identify opportunities for mission improvement
- Support the design and development of agentic AI systems, including autonomous agents capable of multi\-step planning, tool use, and orchestrated task execution within mission workflows
Full\-Stack Application Development:
- Build and maintain web application features using modern frontend frameworks (e.g., React, TypeScript) and backend frameworks (e.g., Python, FastAPI)
- Design and implement RESTful APIs and contribute to database design and query optimization (e.g., PostgreSQL)
- Write clean, testable, and well\-documented code following team coding standards and established design patterns
- Participate in code reviews, sprint planning, and collaborative development within an Agile workflow
CI/CD and DevSecOps:
- Contribute to the development and maintenance of CI/CD pipelines for automated testing, security scanning, and deployment
- Support containerized application builds and deployments using Docker and container orchestration platforms (e.g., Kubernetes)
- Assist with static application security testing (SAST) integration and remediation of findings within the development pipeline
- Help maintain and improve infrastructure\-as\-code configurations and deployment automation scripts
Collaboration and Communication:
- Collaborate with the AI and Automation team to plan, estimate, and deliver work in iterative development cycles
- Document technical designs, implementation decisions, and operational procedures for team and stakeholder reference
- Support demonstrations, briefings, and technical reviews for program leadership and government stakeholders
Required Qualifications:Education:
- Bachelor's degree in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, or a closely related technical field.
Experience:
- 0 to 3 years of professional experience in software development, AI/ML engineering, or a related technical role (internship and academic project experience considered)
Technical Skills:
- Proficiency in Python and at least one modern web development language or framework (e.g., JavaScript/TypeScript, React)
- Foundational understanding of AI/ML concepts, including natural language processing (NLP), large language models (LLMs), embeddings, and vector search
- Experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server) and RESTful API design
- Familiarity with version control systems (Git) and collaborative development workflows (branching strategies, merge requests, code reviews)
- Basic understanding of containerization (Docker) and container orchestration concepts (Kubernetes)
- Familiarity with CI/CD pipeline concepts and at least one CI/CD platform (e.g., GitLab CI/CD, GitHub Actions, Azure DevOps, Jenkins)
- Exposure to at least one cloud platform (AWS, Microsoft Azure, or Google Cloud) and general understanding of cloud\-native application architecture
Security Clearance:
- Ability to obtain and maintain an Active or Interim U.S. Department of War SECRET security clearance prior to joining.
- Must be a U.S. citizen.
Certification:
- Must obtain CompTIA Security\+ certification prior to start date.
Certifications (any of the following are a plus):
- AWS Certified Machine Learning \- Specialty or AWS Certified Solutions Architect \- Associate
- Google Cloud Professional Machine Learning Engineer or Google Cloud Associate Cloud Engineer
- Microsoft Certified: Azure AI Engineer Associate or Azure Developer Associate
Work Environment:
- On\-site position at a U.S. government facility in Huntsville, AL
- Small, collaborative team environment with direct mentorship from senior engineers
- Opportunity to contribute to meaningful mission outcomes through hands\-on engineering of AI\-driven solutions
- Fast\-paced environment where you will be encouraged to learn, experiment, and grow your technical capabilities
Other Responsibilities:
- Perform other duties as assigned
Our Equal Employment Opportunity Policy
The company is an equal opportunity employer. The company shall not discriminate against any employee or applicant because of race, color, religion, creed, ethnicity, sex, sexual orientation, gender or gender identity (except where gender is a bona fide occupational qualification), national origin or ancestry, age, disability, citizenship, military/veteran status, marital status, genetic information or any other characteristic protected by applicable federal, state, or local law. We are committed to equal employment opportunity in all decisions related to employment, promotion, wages, benefits, and all other privileges, terms, and conditions of employment.
The company is dedicated to seeking all qualified applicants. If you require an accommodation to navigate or apply for a position on our website, please get in touch with Heaven Wood via e\-mail at accommodations@koniag\-gs.com or by calling 703\-488\-9377 to request accommodations.
Koniag Government Services (KGS) is an Alaska Native Owned corporation supporting the values and traditions of our native communities through an agile employee and corporate culture that delivers Enterprise Solutions, Professional Services and Operational Management to Federal Government Agencies. As a wholly owned subsidiary of Koniag, we apply our proven commercial solutions to a deep knowledge of Defense and Civilian missions to provide forward leaning technical, professional, and operational solutions. KGS enables successful mission outcomes for our customers through solution\-oriented business partnerships and a commitment to exceptional service delivery. We ensure long\-term success with a continuous improvement approach while balancing the collective interests of our customers, employees, and native communities. For more information, please visit www.koniag\-gs.com.
Equal Opportunity Employer/Veterans/Disabled. Shareholder Preference in accordance with Public Law 88\-352
Salary Context
This $100K-$130K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 2064 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 3,963 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Koniag Government Services, 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 $180,000 based on 12,398 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $163,400. This role's midpoint ($115K) sits 36% below the category median. Disclosed range: $100K to $130K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($290,000) and AI Safety ($274,200). By seniority level: Entry: $97,760; Mid: $163,400; Senior: $227,400; Director: $244,800; VP: $250,000.
Koniag Government Services AI Hiring
Koniag Government Services has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Huntsville, AL, US. Compensation range: $130K - $130K.
Location Context
Across all AI roles, 15% (593 positions) offer remote work, while 3,349 require on-site attendance. Top AI hiring metros: New York (2,585 roles, $210,300 median); San Francisco (2,103 roles, $253,000 median); Los Angeles (1,764 roles, $190,500 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 3,963 open positions tracked in our dataset. By seniority: 116 entry-level, 1,875 mid-level, 1,532 senior, and 440 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (593 positions). The remaining 3,349 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($290,000 median, 39 roles); AI Safety ($274,200 median, 52 roles); Research Engineer ($260,000 median, 421 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 3,963 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,783), Data Scientist (297), AI Software Engineer (279). 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 (116) are outnumbered by mid-level (1,875) and senior (1,532) 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 440 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (593 positions), with 3,349 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 $200,000. Top-quartile roles start at $253,000, 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 Engineering Manager roles lead at $290,000 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 (2,043 postings), Aws (1,241 postings), Azure (934 postings), Rag (886 postings), Gcp (774 postings), Pytorch (614 postings), Prompt Engineering (614 postings), Claude (564 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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