Software Engineer - Data, AI/ML & Analytics

Position: AI/ML Engineer

Location: Washington, DC Metro Area (Hybrid/Onsite based on customer requirements)

Employment Type: Full-Time

Salary: Commensurate with Experience

About VERSA Integrated Solutions

VERSA Integrated Solutions is a premier provider of Information Technology, Artificial Intelligence, Cybersecurity, Cloud, Data Analytics, and Engineering services supporting Federal Government agencies. We help agencies modernize operations through innovative technologies, secure architectures, and mission-driven solutions. Our teams work on high-impact initiatives that improve decision-making, operational efficiency, and citizen services.

Position Summary

VERSA Integrated Solutions is seeking an experienced AI/ML Engineer to design, develop, deploy, and maintain Artificial Intelligence (AI) and Machine Learning (ML) solutions supporting Federal Government customers. The successful candidate will work closely with data scientists, software engineers, cloud architects, cybersecurity professionals, and business stakeholders to build intelligent applications that leverage predictive analytics, machine learning, generative AI, and large language models (LLMs).

The AI/ML Engineer will support the full lifecycle of AI solutions - from data preparation and model development to deployment, monitoring, optimization, and governance - while ensuring compliance with federal security, privacy, and Responsible AI requirements.

Position Objectives

The AI/ML Engineer will:

Design and implement scalable AI and ML solutions.• Build and optimize machine learning models for structured and unstructured data.• Develop data pipelines to support AI workloads.• Integrate AI capabilities into enterprise applications.• Ensure AI solutions comply with federal security, privacy, and governance requirements.• Collaborate with cross-functional teams to deliver mission-focused outcomes.

Major Duties & Responsibilities

AI & Machine Learning Development

Design, develop, train, test, and deploy machine learning models.• Build supervised, unsupervised, reinforcement learning, and deep learning solutions.• Develop predictive analytics and classification models.• Optimize model performance and accuracy through feature engineering and hyperparameter tuning.• Build reusable AI components and services.

Generative AI & Large Language Models

Develop solutions using Large Language Models (LLMs).• Implement Retrieval-Augmented Generation (RAG) architectures.• Engineer prompts and fine-tune models where appropriate.• Evaluate AI model outputs for accuracy, explainability, and bias.• Support secure deployment of generative AI capabilities.

Data Engineering & Preparation

Build and maintain data ingestion and transformation pipelines.• Clean, normalize, and prepare structured and unstructured datasets.• Collaborate with Data Engineers to optimize data availability and quality.• Implement feature stores and model-ready datasets.

MLOps & Model Lifecycle Management

Automate model training, testing, deployment, and monitoring.• Develop CI/CD pipelines for machine learning solutions.• Monitor model drift, performance degradation, and retraining needs.• Maintain version control for models, datasets, and code.

Responsible AI & Governance

Implement Responsible AI principles including fairness, transparency, explainability, and accountability.• Ensure compliance with NIST AI Risk Management Framework, Executive Orders, and agency-specific AI policies.• Document AI models, assumptions, limitations, and validation results.

Collaboration & Innovation

Partner with software developers, cloud engineers, and business analysts to integrate AI into enterprise solutions.• Present technical findings and recommendations to stakeholders.• Evaluate emerging AI technologies and recommend improvements.

Required Technical Skills

Python• SQL• TensorFlow• PyTorch• Scikit-learn• Pandas• NumPy• Hugging Face Transformers• LangChain or similar orchestration frameworks• Azure AI Services or Azure Machine Learning• AWS SageMaker (preferred)• Git/GitHub• Docker• Kubernetes• RESTful APIs

Preferred Skills

Experience with Retrieval-Augmented Generation (RAG)• Prompt engineering for LLMs• Vector databases (e.g., Pinecone, Azure AI Search)• Knowledge graph integration• Natural Language Processing (NLP)• Computer Vision• Time-series forecasting• Knowledge of FedRAMP and Zero Trust environments

Required Qualifications

Strong analytical and problem-solving skills.• Excellent written and verbal communication skills.• Ability to translate business requirements into AI-driven technical solutions.• Experience working in Agile/DevSecOps environments.• Experience supporting federal government customers is highly desirable.

Education

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Mathematics, Statistics, or a related field. A Master's degree is preferred. Equivalent experience may be substituted for education.

Experience Levels

Junior (0–4 Years)

Experience with Python and machine learning fundamentals.• Exposure to cloud platforms and data science tools.• Participation in AI/ML projects through coursework, internships, or professional experience.

Intermediate (5–9 Years)

Development and deployment of production AI/ML models.• Experience with MLOps pipelines and cloud AI services.• Collaboration with cross-functional software development teams.

Senior (10–14 Years)

Leadership in designing enterprise AI solutions.• Expertise in generative AI, LLMs, and Responsible AI practices.• Experience mentoring junior engineers and leading technical initiatives.

Subject Matter Expert (15+ Years)

Recognized authority in enterprise AI strategy and implementation.• Experience shaping AI governance and modernization initiatives for large organizations.• Trusted advisor to executive leadership on AI adoption and emerging technologies.

Preferred Certifications

Microsoft Certified: Azure AI Engineer Associate• Microsoft Certified: Azure Data Scientist Associate• AWS Certified Machine Learning – Specialty• Google Professional Machine Learning Engineer• TensorFlow Developer Certificate• Databricks Certified Machine Learning Professional• ITIL® 4 Foundation (preferred)

Desired Federal Experience

Experience supporting one or more of the following agencies is highly desirable:

U.S. Census Bureau• National Institutes of Health (NIH)• Centers for Medicare & Medicaid Services (CMS)• Department of Commerce• Department of Homeland Security (DHS)• Department of Defense (DoD)• Department of Labor (DOL)

Security Clearance

Ability to obtain and maintain a Public Trust or higherclearance, depending on customer requirements.

Work Environment

Hybrid or onsite within the Washington, DC Metro Area based on customer requirements.• Collaborative, fast-paced environment supporting mission-critical federal AI initiatives.• Occasional travel to customer sites may be required.

Why Join VERSA?

At VERSA, you'll work alongside experts delivering innovative AI solutions that help federal agencies solve complex mission challenges. We invest in continuous learning, professional certifications, and opportunities to work with cutting-edge technologies, including machine learning, generative AI, cloud platforms, and advanced analytics.

Pay: $118,467.98 - $142,671.13 per year

Benefits:

401(k)

401(k) matching

Dental insurance

Health insurance

Paid time off

Retirement plan

Work Location: Hybrid remote in Washington, DC 20591