AI Engineer

Platinum Technologies•Washington, DC

25d•$160,000 - $180,000•Hybrid

About The Position

Platinum Technologies is seeking an AI Engineer to join our company. The AI Engineer will architect and deliver AI and data solutions that solve real mission challenges for federal agencies, from intelligent document retrieval to secure multi-cloud ML platforms. The ideal candidate will be an experienced AI practitioner – with 4+ years of hands-on experience and is comfortable designing AI solutions that are cloud-agnostic, portable across environments, and resilient to vendor lock-in. You will join our established AI and data solutions development team and contribute your expertise in data science, machine learning, cloud-native architecture, and Generative AI technologies to help drive innovation across federal environments. Your focus will include Machine Learning, Natural Language Processing, Neural Networks, Large Language Models (LLMs), Knowledge Graphs, Retrieval-Augmented Generation (RAG), Multi-Modal AI, and modern AI-enabled web applications. This role is remote/hybrid in the VA/MD/DC area. There may be occasional travel to client site in Washington D.C. Required Clearance: Active Public Trust or eligible to obtain on

Requirements

B.S. in Computer Science, Electrical Engineering, Computer Engineering, Data Science, or equivalent experience.
4+ years of experience designing and deploying secure AI and cloud-native solutions in enterprise or federal environments.
Experience working across multiple cloud providers including Azure, AWS, and/or Google Cloud Platform (GCP).
Strong understanding of cloud portability, platform abstraction, Kubernetes/container orchestration, and strategies to avoid vendor lock-in.
Experience designing AI/ML solutions that are LLM-agnostic and capable of integrating with multiple commercial and open-source models (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.).
Experience with Google Vertex AI, AWS Bedrock, Azure AI Foundry, or equivalent AI platform services.
Experience deploying AI workloads on Kubernetes or OpenShift.
Experience with open-source LLM hosting and inference optimization.
Familiarity with MCP (Model Context Protocol), AI orchestration frameworks, and agentic workflows.
Demonstrated experience modernizing web applications using modern front-end and back-end frameworks along with AI-assisted software development tooling.
Strong full-stack engineering capabilities, including user interface development, API design, backend services, and secure application integration.
Experience building conversational AI systems, intelligent search platforms, and enterprise knowledge assistants using RAG architecture.
Experience with vector databases, semantic search technologies, and enterprise search platforms.
Proficiency with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face, or similar ecosystems.
Experience with Infrastructure as Code (Terraform preferred), CI/CD pipelines, containerization, and DevSecOps practices.
Familiarity with AI observability, model evaluation, prompt engineering, and AI governance practices.
Experience implementing secure AI systems in regulated federal environments.
Knowledge of federal compliance and security frameworks including FISMA, RMF, FedRAMP, NIST 800 series, Zero Trust Architecture, and cloud security controls.
Strong oral and written communication skills, including client-facing presentations, architecture discussions, and technical strategy development.

Nice To Haves

Experience supporting federal digital transformation or modernization initiatives.
Experience designing secure hybrid-cloud or disconnected AI environments for government clients.
Familiarity with AI Act and AI governance policy.
Prior experience in consulting or client-facing delivery

Responsibilities

Design and implement AI solutions that operate across multi-cloud and hybrid environments, including Azure, Google Cloud Platform (GCP), and AWS.
Evaluate and recommend hosting, infrastructure, and deployment architectures based on mission requirements, security posture, scalability, portability, and long term maintainability – not tied to a single cloud provider.
Architect AI/ML platforms and applications using cloud-native and containerized technologies that minimize vendor lock-in and maximize interoperability.
Build and modernize web applications using modern full-stack frameworks and AI assisted development tooling to accelerate delivery and improve developer productivity.
Develop sophisticated conversational AI and knowledge management solutions that enable users to securely interact with enterprise data using natural language.
Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases, semantic search, knowledge graphs, and document processing pipelines.
Lead the design of secure cloud and on-premises AI infrastructure solutions that meet Federal Government and internal compliance requirements.
Define architectural design decisions affecting infrastructure selection, orchestration, model hosting, observability, scalability, and system behavior for AI enabled solutions.
Analyze client requirements and emerging AI technology trends to recommend scalable, compliant, and future-proof architectures.
Participate in design thinking and solution engineering activities to solve complex mission and operational challenges.
Lead whiteboarding and technical strategy sessions with clients, partners, and internal teams.
Communicate findings and recommendations to both technical and non-technical stakeholders, translating complex AI and infrastructure concepts into actionable guidance.
Ensure infrastructure and application architectures support secure software delivery practices including CI/CD, Infrastructure as Code (IaC), automated testing, and model lifecycle management.