AI / Machine Learning Engineer

CyberMedia Technologies; United States; Remote; USD 100,000 - 130,000; Full time

Benefits offered by this job

Paid vacation & Sick leave

Health insurance coverage

Performance bonus programs

401K contribution & Employer Match

Job summary

A technology firm is seeking an experienced AI/Machine Learning Engineer to develop systems for automating health benefits determinations for federal clients. The role focuses on integrating large language models with rule-driven patterns, requiring expertise in Machine Learning, Python, and data engineering. This position offers a chance to work on significant federal projects, making a daily impact on millions of citizens. Competitive compensation and benefits are provided, including health insurance and performance bonuses.

Qualifications

• 5–8+ years in Machine Learning or Data Science.
• At least 2 years of hands-on experience with LLMs.
• Experience implementing Generative AI solutions.

Responsibilities

• Design and deploy autonomous AI agents for benefit policies.
• Develop layers synchronizing LLM outputs with business rules.
• Implement advanced Retrieval-Augmented Generation solutions.

Skills

Machine Learning experience

Hands-on experience with LLM orchestration

Proficiency in Python

Strong SQL skills

Analytical Rigor

Education

Bachelor’s degree in Computer Science, Data Science, Engineering or related discipline

Tools

LangChain

LangGraph

CrewAI

Semantic Kernel

PyTorch

TensorFlow

Scikit-learn

Spark/PySpark

Job description

Overview

CTEC is a leading technology firm that provides modernization, digital transformation, and application development services to the U.S. Federal Government. Headquartered in McLean, VA, CTEC has over 300 team members working on mission-critical systems and projects for agencies such as the Department of Homeland Security, Internal Revenue Service, and the Office of Personnel Management. The work we do effects millions of U.S. citizens daily as they interact with the systems we build. Our best-in-class commercial solutions, modified for our customers’ bespoke mission requirements, are enabling this future every day.

The Company has experienced rapid growth over the past 3 years and recently received a strategic investment from Main Street Capital Corporation (NYSE: MAIN). In addition to our recent growth in Federal Civilian agencies, we are seeking to expand our capabilities in cloud development and footprint in national-security focused agencies within the Department of Defense and U.S. Intelligence Community.

We are seeking to hire an AI/Machine Learning Engineer to our team!

Role Overview

As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits determinations for the Office of Personnel Management (OPM). Your work will focus on marrying the reasoning capabilities of Large Language Models (LLMs) with deterministic, rule-driven patterns to ensure accuracy, auditability, and compliance in complex decision-making workflows.

Duties and Responsibilities

• Agentic System Architecture: Design and deploy autonomous AI agents capable of multi-step reasoning, tool-use, and self-correction to navigate complex federal benefit policies.
• Deterministic Logic Integration: Develop "Guardrail" layers that synchronize probabilistic LLM outputs with rigid business rules, ensuring benefit determinations adhere strictly to legal and regulatory frameworks.
• RAG & Knowledge Engineering: Implement advanced Retrieval-Augmented Generation (RAG) solutions, utilizing layout-aware parsing to extract information from dense manuals/documentation and unstructured data.
• Hybrid Model Development: Design and evaluate machine learning models that support both data-driven predictions and symbolic/rule-based automation.
• MLOps & Agent Monitoring: Deploy models into cloud environments with a focus on LLM-specific observability (tracing reasoning loops, monitoring for hallucinations, and detecting data drift in logic).
• Auditability & Explainability: Ensure every AI-driven determination has a clear, human-readable "audit trail" or reasoning chain that justifies the outcome based on source documentation.
• Collaboration: Work alongside solution architects and business stakeholders to translate complex health insurance policies into executable AI logic.

Skills & Work Experience

• Professional Experience: 5–8+ years in Machine Learning or Data Science, with at least 2 years of hands-on experience with LLM orchestration and Generative AI frameworks.
• Agentic Frameworks: Proficiency with tools such as LangChain, LangGraph, CrewAI, or Semantic Kernel for building multi-step agent workflows.
• Core Development: Strong proficiency in Python and experience with standard frameworks (PyTorch, TensorFlow, or Scikit-learn)
• Data Engineering: Strong SQL skills and experience with distributed data processing (Spark/PySpark) to handle large-scale enterprise data.
• Analytical Rigor: Ability to debug non-deterministic systems and implement rigorous evaluation frameworks (e.g., RAGAS, LLM-as-a-judge) data platforms.

Preferred

• Experience with Azure Machine Learning, Azure AI services, or similar cloud AI platforms.
• Experience implementing Generative AI, LLM, or RAG-based solutions.
• Experience supporting federal IT modernization or data transformation programs.
• Familiarity with healthcare, insurance, or benefits administration data environments.
• Experience applying data governance, privacy, and security best practices in AI/ML solutions.

Education

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related discipline. Master’s degree preferred. Equivalent professional experience will be considered in lieu of a degree.

Clearance

Must be a U.S. citizen and be able to obtain an OPM Public Trust clearance.

Compensation and Benefits

In addition to employee salary, we offer an array of employee benefits including:

• Paid vacation & Sick leave
• Health insurance coverage
• Performance bonus programs
• 401K contribution & Employer Match

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. We do not discriminate on the basis of protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we collect this information to measure the effectiveness of outreach and recruitment efforts. Classification of protected categories is as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.

Public burden statement: According to the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.