Fantom

Systems integration and IT services, analytics

AI Engineer - Subject Matter Expert

Applied Machine Learning +1Posted on Nov 13

Full-timeChantilly, VA, USANo salary listed

About the Job

Requirements

A bachelor's degree is required.
At least 10 years of specialized AI/ML engineering experience is required.
Advanced Python skills and a strong understanding of algorithms, data structures, and distributed systems are required.
Hands-on experience deploying production generative AI and large language model systems, embeddings, and vector databases is required.
Proficiency with PyTorch, TensorFlow, and scikit-learn is required.
Experience with one or more cloud platforms, including AWS, Azure, or Google Cloud, is required.
Practical experience with MLOps tools such as MLflow, Azure Machine Learning, or Vertex AI is required.
A background in natural language processing, computer vision, or reinforcement learning is required.
Experience with CI/CD, containerization, model deployment, and production monitoring is required.
Experience working in Agile engineering environments is required.
The ability to mentor engineers and coordinate technical standards across teams is required.
Experience with multimodal orchestration, AI implementations for temporal, spatial, geographic, quantitative, and computer vision tasks, named entity recognition, contextual entity extraction, and entity resolution is required.
Experience with multi-step retrieval, structured output generation, complex data parsing, detailed source citation, traceable analytical outputs, data ingestion, normalization, and ETL pipeline creation, scheduling, and optimization is required.
Experience integrating vector, graph, and relational databases, and implementing attribute-based access control, data provenance, and end-to-end data lineage tracking is required.
Experience with air-gapped, hybrid, or on-premises environments, Kubernetes, locally hosted GPU servers, hyperconverged nodes, and multitenant cross-domain solutions is required.
Experience with user interface, backend, and middleware engineering using TypeScript, React, Python, and FastAPI is required.
Experience integrating LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes is required.
The candidate must possess an active Top Secret clearance and be willing and able to obtain a polygraph.

Responsibilities

Build scalable AI/ML and generative AI models, pipelines, and microservices for production use.
Develop training, evaluation, and inference pipelines in Python using PyTorch, TensorFlow, or scikit-learn.
Deploy and manage models using MLOps tools, CI/CD pipelines, containerization, and monitoring frameworks.
Implement embeddings, vector databases, large language model applications, agentic AI, and tool-calling workflows.
Develop multi-model and multimodal capabilities spanning reasoning, perception, memory, and tool execution.
Implement temporal, spatial, geographic, quantitative, and computer vision AI capabilities.
Develop named entity recognition, contextual entity extraction, and entity resolution workflows.
Build multi-step retrieval and structured output generation capabilities with detailed source citations and traceable analytical outputs.
Create and optimize data parsing, ingestion, normalization, and ETL pipelines for structured and unstructured data.
Integrate vector, graph, and relational databases while supporting data provenance, lineage, and attribute-based access control.
Optimize models and services for accuracy, latency, cost, and scalability across distributed environments.
Integrate user interfaces, backend services, middleware, databases, and AI components within the custom application.
Support deployment across air-gapped, hybrid, and on-premises environments, including locally hosted GPU infrastructure.
Maintain technical documentation and align development with AI governance, ethical requirements, and security standards.
Mentor engineers and establish consistent engineering practices across teams.

Desired Qualifications

Experience supporting federal, defense, or highly regulated environments is preferred.
Knowledge of ethical AI, governance frameworks, and secure development practices is preferred.
Experience with large-scale optimization, GPU acceleration, or distributed training is preferred.
Experience building APIs, microservices, and automated machine learning workflows is preferred.

Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth.

Must possess an active Top Secret Clearance

Must be willing and able to obtain a polygraph

Education: Bachelor’s degree required
Experience: Minimum of 10 years of specialized AI/ML engineering experience

Position Summary

We are seeking a Senior AI/ML Engineer to build and deploy scalable, production-ready artificial intelligence, machine learning, and generative AI capabilities. This role develops models, pipelines, and microservices that support LLM applications, agentic workflows, and advanced analytics.

The engineer will support an in-house custom application, integrating AI services, retrieval systems, databases, and application components across secure operational environments. The position requires hands-on engineering, technical mentorship, and collaboration across teams to improve model performance, reliability, security, and maintainability.

Responsibilities

Build scalable AI/ML and generative AI models, pipelines, and microservices for production use.

Develop training, evaluation, and inference pipelines in Python using PyTorch, TensorFlow, or scikit-learn.

Deploy and manage models using MLOps tools, CI/CD pipelines, containerization, and monitoring frameworks.

Implement embeddings, vector databases, LLM applications, agentic AI, and tool-calling workflows.

Develop multi-model and multimodal capabilities spanning reasoning, perception, memory, and tool execution.

Implement temporal, spatial, geographic, quantitative, and computer vision AI capabilities.

Develop named entity recognition, contextual entity extraction, and entity resolution workflows.

Build multi-step retrieval and structured output generation capabilities with detailed source citations and traceable analytical outputs.

Create and optimize data parsing, ingestion, normalization, and ETL pipelines for structured and unstructured data.

Integrate vector, graph, and relational databases while supporting data provenance, lineage, and attribute-based access control.

Optimize models and services for accuracy, latency, cost, and scalability across distributed environments.

Integrate user interfaces, backend services, middleware, databases, and AI components within the custom application.

Support deployment across air-gapped, hybrid, and on-premises environments, including locally hosted GPU infrastructure.

Maintain technical documentation and align development with AI governance, ethical requirements, and security standards.

Mentor engineers and establish consistent engineering practices across teams.

Required Qualifications

Must possess an active Top Secret Clearance
Must be willing and able to obtain a polygraph
Minimum of 10 years of specialized AI/ML engineering experience.
Advanced Python skills and a strong understanding of algorithms, data structures, and distributed systems.
Hands-on experience deploying production generative AI and LLM systems, embeddings, and vector databases.
Proficiency with PyTorch, TensorFlow, and scikit-learn.
Experience with one or more cloud platforms, including AWS, Azure, or Google Cloud.
Practical experience with MLOps tools such as MLflow, Azure Machine Learning, or Vertex AI.
Background in natural language processing, computer vision, or reinforcement learning.
Experience with CI/CD, containerization, model deployment, and production monitoring.
Experience working in Agile engineering environments.
Ability to mentor engineers and coordinate technical standards across teams.

Technical Requirements

Advanced AI and Generative AI Engineering

Multi-model and multimodal orchestration for reasoning, perception, memory, and tool execution.

Temporal, spatial, geographic, quantitative, and computer vision AI implementation.

Named entity recognition, contextual entity extraction, and entity resolution.

Multi-step retrieval and structured output generation.

Complex data parsing and streamlined ingestion.

Detailed source citation and traceable analytical outputs.

Data Architecture and ETL

Vector, graph, and multiple database orchestration.

Automated ETL pipeline creation, scheduling, and optimization.

Attribute-based access control (ABAC) at the data layer.

Provenance and end-to-end data lineage tracking.

Schema-aligned ingestion and normalization of diverse structured and unstructured data.

Enterprise Infrastructure and Cross-Domain Solutions

Air-gapped, hybrid, and on-premises operational environments.

Container orchestration and distributed systems management using Kubernetes.

Locally hosted GPU servers and hyperconverged nodes.

Multitenant cross-domain solutions (CDS).

Application Development and Integration

User interface, backend, and middleware engineering using TypeScript, React, Python, and FastAPI.

Integration with LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.

Integration of reasoning components, retrieval systems, databases, and AI and generative AI services.

Development and maintenance of an in-house custom application using modern programming languages and frameworks.

Preferred Qualifications

Experience supporting federal, defense, or highly regulated environments.

Knowledge of ethical AI, governance frameworks, and secure development practices.

Experience with large-scale optimization, GPU acceleration, or distributed training.

Experience building APIs, microservices, and automated machine learning workflows.

#CJ

Fantom Corp is a Software Development, Agile Cloud, Software Development, Cyber Security (Risk Management, Assessments & Authorization (A&A)), Data, AI Platform (Computer Vision Models), Podcasting Media Services, and IT Services provider. Established in 2015, Fantom Corp serves Federal customers with top-notch Cybersecurity Architects, Data Scientists/Analysts, Software Engineers/Developers, DevSecOps Engineers, Project Managers, Identity, Credential Access Management (ICAM) services , and Cloud-certified practitioners. We excel in delivering emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) with a focus on identifying trends, object detection, and classification of structured and unstructured data. Fantom Corp possesses mastery in all aspects of digital audio production. We lead in the ideation and creation of efforts for clients who want to harness the power of podcasting. We guide them in selecting the right show format for their needs and goals. As a Small Business, we possess the innovation, speed and flexibility to meet your requirements.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

About the Company

Fantom

Systems integration and IT services, analytics

Fantom leads IT services for federal and commercial clients, focusing on big data analytics, system integration, software engineering, and technical consulting. Its offering blends architecture and program management with data-driven capabilities to help organizations detect patterns, uncover trends, and derive actionable insights from structured and unstructured data. Projects are delivered through service contracts and fixed engagements, supported by a team of architects, engineers, and program managers. What sets Fantom apart is its minority-owned status combined with a dual focus on Department of Defense and Intelligence Community work alongside private-sector clients, and its emphasis on employee well-being through benefits like profit-sharing and life insurance. The company's goal is to enable clients to make informed decisions and achieve mission and business objectives by providing specialized IT solutions and data-driven capabilities.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Leesburg, VA
Founded: 2014

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