AI/ML Engineer IV

Kentro

Northern (KY)

Hybrid

USD 165,000 - 196,000

Full time

25 hours ago
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Benefits offered by this job

Healthcare benefits
401k with employer match
Education reimbursement
Flexible work arrangements

Job summary

Kentro is hiring an AI/ML Engineer IV to serve as lead AI/ML engineer on the FAA ATLAS program. You will define AI strategy, architect a shared AI platform, and drive AI modernization across a large portfolio.

This role emphasizes responsible AI, governance, and collaboration with architecture, cybersecurity, and program leadership. Remote within the United States with ET hours.

Qualifications

  • Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related technical discipline.
  • 8–10 years of progressive software engineering and AI/ML experience with production ML systems.
  • Proven record delivering machine learning systems into production.
  • Expert proficiency in Python and the modern ML stack (PyTorch or TensorFlow, scikit‑learn, pandas).
  • Deep MLOps/LLMOps experience: training/deployment pipelines, model/versioning, evaluation, monitoring.
  • Experience with large language models in production and cost/latency management.

Responsibilities

  • Define and lead the AI/ML engineering strategy for the portfolio.
  • Architect the shared AI engineering platform as a reusable capability.
  • Establish end-to-end MLOps: CI/CD for models, data/model versioning, reproducibility.
  • Lead AI-assisted modernization: code comprehension, document recovery, automated refactoring.
  • Design and deliver production AI capabilities for modernized systems.
  • Implement governance and responsible AI practices with policy alignment.
  • Define model evaluation standards and monitoring for production models.
  • Advise FAA stakeholders on AI feasibility and expectations.

Skills

Technical leadership
Mentoring
Communication
Problem solving

Education

Bachelor's degree in CS/DS/ML/Stats/Math

Tools

Python
PyTorch
TensorFlow
scikit-learn
Pandas
SageMaker
OpenAI Service
Vertex AI

Job description

Overview

Thank you for considering IT Concepts dba Kentro, where innovation drives opportunity and collaboration leads to success. Our dynamic community of experts is fully committed to advancing our customers' missions, fostering professional growth, and making a positive impact on our communities.

By joining our supportive community, you will find that Kentro is dedicated to your personal and professional development. Together, we can drive meaningful change, spark innovation, and achieve extraordinary milestones.

Kentro is hiring an AI/ML Engineer IV to serve as lead AI/ML engineer on the Federal Aviation Administration’s (FAA) Accelerated Transformation of Legacy Applications and Systems (ATLAS) program — one of the largest civilian IT modernization efforts in the federal government. ATLAS covers a mission-support portfolio of more than 200 applications and roughly 3,000 databases, and artificial intelligence is named directly in the modernization objectives: intelligent automation, enterprise data excellence, and AI integrated into how the portfolio is both transformed and operated.

In this role you define the AI engineering strategy and shared AI platform architecture for the program in alignment with enterprise architecture, data governance, cybersecurity, and program priorities. You bring mastery of AI/ML technologies, MLOps, and responsible AI practice, and you apply it to two distinct problems: using AI to accelerate the modernization itself — code understanding, automated transformation, test generation, documentation recovery from undocumented legacy systems — and building the AI capabilities that modernized FAA systems will run on.

You lead AI initiatives across the portfolio, establish shared AI engineering capabilities that other teams build on, drive innovation from pilot through production, and provide technical leadership for AI transformation. In a federal aviation context that means governance is not an afterthought: every model you put into production has to be explainable, monitored, documented, and defensible under federal AI policy.

Location: Remote - This position can be performed remotely within the United States and will support Eastern Time working hours.

Compensation Range: The pay range for this position is $165,000-196,000 annually. Kentro determines compensation by evaluating current government contracting and commercial market conditions, as well as the role’s specific requirements. Final salary placement within this range will be based on the candidate’s relevant skills, experience, education, certifications, location, and security clearance level, where applicable.

This Job Description reflects the primary duties of the role; however, it is not intended to be all‑inclusive. Team members may be asked to take on additional responsibilities in alignment with customer expectations, business needs, and Kentro’s culture of collaboration and adaptability.

Responsibilities
  • Define and lead the AI/ML engineering strategy for the portfolio in alignment with enterprise architecture, data governance, cybersecurity, and program priorities; determine where AI creates measurable value and sequence capabilities accordingly
  • Architect the shared AI engineering platform — approved model and provider access, prompt and agent orchestration, retrieval-augmented generation, evaluation, model registry and serving, monitoring, and traditional training infrastructure where justified — as shared capability rather than per-project tooling
  • Establish end-to-end MLOps practice: automated training and evaluation pipelines, CI/CD for models, versioning of data, code and models, reproducibility, and controlled promotion to production
  • Lead AI-assisted modernization initiatives: apply LLMs and code-transformation tooling to legacy code comprehension, documentation recovery, automated refactoring, test generation, and data model inference across a large enterprise including legacy systems
  • Design and deliver production AI capabilities for modernized systems, including retrieval-augmented generation, document and text processing, classification, forecasting, and anomaly detection
  • Implement the technical controls that support the program’s responsible AI practice, in partnership with architecture, cybersecurity, data governance, and program leadership: bias and fairness evaluation, explainability, human-in-the-loop design, model cards and documentation, red-teaming, and pre-deployment risk assessment
  • Engineer AI systems to satisfy applicable federal obligations, including OMB AI policy for federal agency use (currently M-25-21), the NIST AI Risk Management Framework, FISMA and NIST SP 800-53 controls, and applicable FAA and DOT guidance
  • Define model evaluation standards and the monitoring regime for production models: drift detection, performance degradation, data quality gates, and retraining triggers
  • Define AI workload requirements for the data engineering interface — pipelines, feature stores, labeling strategy, provenance, and data quality — in partnership with the enterprise data architecture lead
  • Recommend which class of AI fits each use case — classical ML, generative AI, or agentic systems — and be responsible for assessing the implications that follow from that choice, including the security boundary and data exposure, privacy and data residency, inference and token cost at scale, evaluation difficulty, and long‑term sustainment burden
  • Lead technical evaluation and recommendations for build-versus-buy and model selection decisions across commercial, open-weight, and cloud-provider models, accounting for cost, latency, data residency, and federal security constraints
  • Drive innovation: identify emerging AI capability, run structured pilots with defined success criteria, and productize what proves out into standard practice
  • Provide technical leadership, design review, and code review to AI/ML engineers and data scientists across delivery teams; mentor engineers new to production ML
  • Advise program leadership and FAA stakeholders on AI feasibility, risk, and realistic expectations
Qualifications
  • Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related technical discipline
  • 8–10 years of progressive software engineering and AI/ML experience, including demonstrated technical leadership on production ML systems
  • Proven record delivering machine learning systems into production and operating them over time — not research or proof‑of‑concept work alone
  • Expert proficiency in Python and the modern ML stack (PyTorch or TensorFlow, scikit‑learn, pandas, and related tooling)
  • Deep MLOps/LLMOps experience: training and deployment pipelines, model and prompt versioning, experiment tracking, automated evaluation, and production monitoring
  • Hands‑on experience with large language models in production, including prompt engineering, retrieval‑augmented generation, fine‑tuning or adaptation, evaluation, and cost and latency management
  • Cloud ML platform expertise (AWS SageMaker/Bedrock, Azure ML/OpenAI Service, or GCP Vertex AI), including containerized and scalable serving architectures
  • Strong data engineering foundation: pipelines, feature engineering at scale, and working with imperfect data from legacy sources
  • Demonstrated judgment in selecting among classical ML, generative AI, and agentic approaches, with the ability to justify the choice on security, privacy, cost, and sustainment grounds
  • Demonstrated application of responsible AI practice — fairness, explainability, documentation, and risk assessment — in a regulated or high‑consequence setting
  • Solid software engineering fundamentals: version control, testing, code review, and CI/CD discipline applied to ML code
  • Ability to set standards other teams adopt, and to communicate AI capability and limitation credibly to non‑technical executive and government audiences
Preferred Qualifications
  • Experience supporting FAA, DOT, or comparable federal civilian programs, particularly where AI governance and ATO processes applied
  • Direct experience applying AI to legacy modernization — code comprehension, automated transformation, or documentation recovery at portfolio scale
  • Familiarity with federal AI governance in practice: OMB AI policy compliance, agency AI use case inventories, and high‑impact AI determinations
  • Experience with the NIST AI Risk Management Framework applied to a real deployment rather than in the abstract
  • Background in aviation, transportation, or another safety‑critical domain
  • Experience standing up an AI/ML engineering platform or AI center of excellence from scratch
  • Relevant certifications: AWS Machine Learning Specialty, Azure AI Engineer, or GCP Professional ML Engineer
  • Experience with agentic systems, tool use, and orchestration frameworks in production
  • Publications, open‑source contributions, or conference presentations in applied ML
Clearance Requirement
  • US Citizen
  • Existing FAA suitability determination or transferable federal background investigation strongly preferred
Benefits
The Company

We believe in generating success collaboratively, enabling long‑term mission success, and building trust for the next challenge. With you as our partner, let’s solve challenges, think innovatively, and maximize impact. As a valued member of our team, you have the unique opportunity to work in a diverse range of technology and business career paths, all while supporting our nation and delivering innovative technology solutions. We are a close community of experts that pride ourselves on creating an environment defined by teamwork, dedication, and excellence.

We hold three ISO certifications (27001:2013, 20000-1:2011, 9001:2015), two CMMI ML 3 ratings (DEV and SVC) and CMMC Level 2 Certification.

Industry Recognition

Growth | Inc 5000’s Fastest Growing Private Companies, DC Metro List Fastest Growing; Washington Business Journal: Fastest Growing Companies, Top Performing Small Technology Companies in Greater D.C.

Culture | Northern Virginia Technology Council Tech 100 Honoree; Virginia Best Place to Work; Washington Business Journal: Best Places to Work, Corporate Diversity Index Winner – Mid-Size Companies, Companies Owned by People of Color; Department of Labor’s HireVets for our work helping veterans transition; SECAF Award of Excellence finalist; Victory Military Friendly Brand; Virginia Values Veterans (V3); Cystic Fibrosis Foundation Corporate Breath Award

Benefits

We offer competitive benefits package including paid time off, healthcare benefits, supplemental benefits, 401k including an employer match, discount perks, rewards, and more. We invest in our employees – Every employee is eligible for education reimbursement for certifications, degrees, or professional development. Reimbursement amounts may fluctuate due to IRS limitations. We want you to grow as an expert and a leader and offer flexibility for you to take a course, complete a certification, or other professional growth and networking. We are committed to supporting your curiosity and sustaining a culture that prioritizes commitment to continuous professional development.

We work hard; we play hard. Kentro is committed to incorporating fun into every day. We dedicate funds for activities – virtual and in‑person – e.g., we host happy hours, holiday events, fitness & wellness events, and annual celebrations. In alignment with our commitment to our communities, we also host and attend charity galas/events. We believe in appreciating your commitment and building a positive workspace for you to be creative, innovative, and happy.

Commitment Equal Opportunity Employment & VEVRAA

Kentro is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state or local law.

Kentro is strongly committed to compliance with VEVRAA and other applicable federal, state, and local laws governing equal employment opportunity. We have developed comprehensive policies and procedures to ensure our hiring practices align with these requirements.

As part of our VEVRAA compliance efforts, Kentro has established an equal opportunity plan outlining our commitment to recruiting, hiring, and advancing protected veterans. This plan is regularly reviewed and updated to ensure its effectiveness.

We encourage protected veterans to self‑identify during the application process. This information is strictly confidential and will only be used for reporting and compliance purposes as required by law. Providing this information is voluntary and will not impact your employment eligibility.

Our commitment to equal employment opportunity extends beyond legal compliance. We are dedicated to fostering an inclusive workplace where all employees, including protected veterans, are treated with dignity, respect, and fairness.

Accommodations

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable Accommodations may be made to enable qualified individuals with disabilities to perform the essential functions. If you need to discuss reasonable accommodations, please email careers@kentro.us.

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