AI/ML Platform Engineer

This is a fully remote position, open to applicants in Virginia.

📋 Description

• Facilitate AI/ML platform services as a managed, multi-tenant enterprise solution encompassing traditional ML, GenAI, and agentic AI.

• Offer regulated access to advanced models via an AI gateway layer, RAG infrastructure, knowledge bases, vector databases, embedding pipelines, per-tenant guardrails, grounding validation, and feedback mechanisms.

• Implement agentic AI frameworks that include orchestration systems, tool/API integration, memory and state management, human-in-the-loop controls, and safety mechanisms.

• Support the operationalization of traditional ML through regulated training environments, model deployment pipelines featuring TAI controls, and comprehensive drift and quality monitoring across fleets.

• Collaborate closely with clients from the initial concept to production handoff, taking ownership of requirements, specifications, solution design, implementation, and delivery.

• Assess and incorporate new AI/ML platform features, tools, and services.

• Create repeatable and portable platform onboarding methodologies and Infrastructure as Code (IaC) templates using Terraform and CloudFormation, including SSO integration.

• Develop secure API-based endpoints for model access and inference that adhere to governance and security standards.

• Document reusable patterns, frameworks, and APIs for future application deployments.

⛳️ Requirements

• Bachelor’s or master’s degree in computer science, Machine Learning, or a related discipline.

• Over 5 years of relevant, hands-on AI/ML engineering experience, actively coding, constructing pipelines, and designing systems across traditional ML, GenAI, and/or agentic AI.

• Proven platform-level thinking and experience in enabling AI/ML functionalities as a managed service, including regulated multi-tenant compute, model deployment pipelines with safeguards, GenAI access layers, or agentic orchestration infrastructure.

• Strong command of Python with practical experience in PyTorch, TensorFlow, HuggingFace, LangChain, or similar technologies.

• Practical experience with cloud-based AI/ML platforms such as Databricks, SageMaker, or equivalents, covering model development, MLOps, data governance, and multi-tenant operationalization.

• Hands-on experience with GenAI and LLM frameworks, RAG pipelines, vector databases, embedding models, prompt engineering, and regulated model access layers.

• Strong skills in IaC and cloud engineering using Terraform, CloudFormation, AWS-native services, enterprise SSO integration, and cloud security practices.

• Familiarity with federal security and governance standards, including FedRAMP, NIST 800-53, and best practices for data isolation.

• Demonstrated ability to work directly with clients, converting ambiguous problem statements into clear requirements, specifications, and effective end-to-end solutions.

• Comfortable operating within regulated environments that have governance requirements and security protocols.

• Preferred: experience with agentic AI frameworks, AI gateway patterns such as LiteLLM, vector databases like Pinecone, FAISS, Weaviate, or Amazon OpenSearch Vector, as well as CI/CD and MLOps methodologies including MLflow, Git, and Docker, along with experience in regulated industries.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Professional development opportunities and support for continuous learning.

• A collaborative and innovative work environment.