AI/ML Engineering Lead

4A Consulting, LLC; Linthicum (MD); On-site; USD 190,000 - 230,000; Full time

Benefits offered by this job

Flexible work options

Comprehensive benefits package

Professional development

Job summary

4A Consulting, LLC seeks an AI/ML Engineering Lead to architect, develop, deploy, and govern a shared enterprise AI/ML platform for multiple state agencies. You will set technical standards, oversee production deployments, and collaborate with engineering teams and policy stakeholders to deliver scalable AI capabilities.

The role emphasizes Generative AI, LLMs, data governance, security, and responsible AI, with strong leadership across ML, data, and platform engineers.

Qualifications

• Bachelor's degree in CS/DS/Engineering, master's preferred.
• 16+ years software/data engineering with 3+ years ML production systems.
• Experience building enterprise AI/ML platforms for multiple teams.
• Strong Python and ML framework experience (PyTorch, TensorFlow, scikit-learn, Hugging Face).

Responsibilities

• Lead architecture and governance of enterprise AI/ML platform.
• Define technical standards and oversee production deployments.
• Design scalable, secure ML infrastructure and CI/CD pipelines.
• Mentor ML, data, and platform engineers and manage incidents.

Skills

Python

ML frameworks

MLOps

Cloud platforms

Kubernetes

CI/CD

Data engineering

FS/Feature stores

Security & governance

GitOps

Education

Bachelor's in CS/DS/Engineering

Master's preferred

Tools

MLflow

Kubeflow

Apache Airflow

Docker

Terraform/Pulumi

SageMaker/Azure/GCP

Job description

At 4A Consulting, we turn complexity into opportunity. Founded in 2014 and headquartered in Baltimore, MD, we are a women-owned, boutique consulting firm specializing in delivering innovative, data-driven solutions to both the Federal Government and Fortune 500 clients. Our team blends deep industry knowledge with advanced technologies to design tailored strategies that drive measurable and sustainable outcomes. We pride ourselves on an agile, collaborative approach that helps organizations navigate challenges and seize emerging opportunities in a rapidly evolving digital landscape. At 4A, we don’t just deliver projects, we build trusted partnerships that empower our clients to lead with confidence in the digital age.

Position Overview

The AI/ML Engineering Lead will lead the architecture, development, implementation, and governance of a shared enterprise Artificial Intelligence and Machine Learning (AI/ML) platform serving multiple state agencies. The role requires strong expertise in ML engineering, MLOps, cloud infrastructure, data engineering, and Generative AI to enable secure, scalable, reliable, and responsible AI/ML solutions. The Lead will establish technical standards, oversee production deployments, and collaborate with engineering teams, agency leadership, and policy stakeholders to deliver enterprise AI capabilities.

Key Responsibilities

• Platform Architecture: Define the technical vision and roadmap; design scalable, secure, and cost-effective AI/ML infrastructure; and evaluate cloud services, frameworks, and tools, including AWS SageMaker and equivalent Azure or GCP services.
• MLOps and Platform Engineering: Build end-to-end ML pipelines for data ingestion, feature engineering, model training, validation, versioning, deployment, and monitoring. Implement CI/CD, automated testing, canary deployments, rollback procedures, model registries, experiment tracking, and production support standards.
• Generative AI and LLMs: Design and deploy LLM and Retrieval-Augmented Generation (RAG) solutions, prompt management, model evaluation, and fine-tuning workflows. Implement safeguards against hallucinations, prompt injection, data exposure, and unfair or inappropriate outputs.
• Data Engineering and Governance: Oversee shared data pipelines, feature stores, data quality, lineage, and access controls. Ensure compliance with applicable state and federal data privacy and security requirements.
• Security and Responsible AI: Integrate identity and access management, encryption, audit logging, model governance, explainability, fairness, and risk assessment into platform operations.
• Technical Leadership and Operations: Lead and mentor ML, data, and platform engineers; establish engineering standards; conduct architecture and code reviews; define service-level objectives and agreements (SLOs/SLAs); manage production incidents; and optimize reliability, performance, scalability, and cost.
• Automation and Continuous Improvement: Implement infrastructure as code, GitOps, observability, and standardized deployment practices. Partner with agency teams to onboard users and accelerate delivery of production-ready AI/ML solutions.

Required Qualifications

• Bachelor\'s degree in Computer Science, Data Science, Engineering, Information Technology, or a related field from an accredited college or university. A master\'s degree is preferred.
• At least sixteen (16) years of software or data engineering experience, including at least three (3) years focused on production ML systems, MLOps, or ML platform engineering.
• At least twelve (12) years of relevant general experience and ten (10) years of specialized IT experience directly related to the required area of expertise, subject to applicable contract labor-category requirements.
• Demonstrated experience building or operating shared enterprise AI/ML platforms supporting multiple teams, departments, or business units.
• Strong proficiency in Python and familiarity with ML frameworks including PyTorch, TensorFlow, scikit-learn, and Hugging Face.
• Hands‑on experience with MLOps and workflow tools such as MLflow, Kubeflow, and Apache Airflow, or equivalent technologies.
• Experience with cloud AI/ML services on AWS, Azure, or GCP, including AWS SageMaker or equivalent managed ML services.
• Experience with Docker, Kubernetes, CI/CD pipelines, model registries, experiment tracking, automated testing, model deployment, and monitoring.
• Working knowledge of LLMs, prompt engineering, RAG architecture, Generative AI evaluation, and fine‑tuning workflows.
• Strong understanding of data engineering, including data pipelines, feature stores, data quality, data lineage, and data governance.
• Experience with infrastructure as code, such as Terraform or Pulumi, and familiarity with GitOps practices.

Preferred Qualifications

• Experience in state government, the public sector, or highly regulated environments.
• Familiarity with FedRAMP, NIST AI Risk Management Framework (AI RMF), and applicable cybersecurity and privacy requirements, including CJIS, HIPAA, IRS Publication 1075, and PII protection, where applicable.
• Experience with responsible AI, model explainability, fairness auditing, bias mitigation, and model risk management.
• Knowledge of platform observability, reliability engineering, incident management, disaster recovery, and cloud cost optimization.
• Strong technical leadership, mentoring, documentation, communication, and cross‑functional collaboration skills, including the ability to explain complex technical concepts to executive and nontechnical stakeholders.

Why Join 4A

• Be part of a mission‑driven, women‑owned consulting firm with a reputation for excellence.
• Work on high‑impact projects across federal and commercial clients.
• Collaborate in an inclusive, growth‑oriented culture where innovation is valued.
• Access career development programs, mentorship, and learning opportunities.
• Enjoy a comprehensive benefits package, flexible work options, and a focus on work‑life balance.

Equal Opportunity Statement

4A Consulting is an Equal Opportunity Employer committed to an inclusive hiring process. Applicants requiring a reasonable accommodation due to a disability may contact [e-mail]. This email is intended solely for accommodation requests.

Please note that 4A Consulting participates in the federal E-Verify program. Upon hire, we will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the US. 4A Consulting will only use E-Verify once you have accepted a job offer and completed the Form I-9.