Job Description

AI Engineer

Experience Level: Senior/Principal (5+ years)

Location: Richmond, VA

Work Authorization/Clearance Requirements: NA

Roles and Responsibilities of this position:

Overview

We are seeking an experienced AI Engineer to join our team and lead the development of cutting-edge artificial intelligence solutions. In this role, you will architect end-to-end AI systems, from proof of concept through production deployment, ensuring they meet performance targets while adhering to ethical AI practices. You will work with cross-functional teams to translate business requirements into scalable AI solutions that deliver real impact.

System Architecture & Development

• Design and implement end-to-end AI architectures including data pipelines, model training infrastructure, and high-performance inference systems.
• Build production-ready AI/ML models with <100ms latency and strong accuracy benchmarks.
• Develop deep learning, NLP, computer vision, and reinforcement learning models.
• Apply model optimization techniques such as quantization, pruning, and knowledge distillation.

Production Deployment

• Deploy AI solutions via REST/gRPC APIs, serverless environments, and edge platforms.
• Set up CI/CD pipelines, automated testing, and model versioning workflows.
• Implement A/B testing, observability dashboards, and continuous improvement loops.
• Ensure 99.9% uptime, SLAs, and reliability for production AI systems.

MLOps & Infrastructure

• Build and operate MLOps infrastructure using MLflow, Kubeflow, or similar platforms.
• Manage model registries, feature stores, and experiment tracking systems.
• Optimize distributed training, GPU resource utilization, and scaling strategies.
• Configure monitoring, alerting, rollbacks, and production governance.

Ethical AI & Governance

• Implement bias detection, fairness metrics, and robustness testing.
• Build explainability tools, documentation, and audit trails.
• Ensure compliance with data privacy and AI governance frameworks.

Collaboration & Leadership

• Collaborate with data scientists, engineers, and product teams for integrated delivery.
• Mentor junior engineers and promote AI best practices.
• Communicate complex AI concepts to technical and business stakeholders.
• Lead architectural reviews and technical decision-making.

Required Qualifications

Education

• Bachelor’s in Computer Science, Engineering, Mathematics, or related field (Master’s preferred).

Experience

• 5+ years building, deploying, and scaling production AI/ML systems.
• Proven experience delivering measurable business impact with AI solutions.
• Strong background in distributed data processing and large-scale systems.

Technical Skills

• Programming: Python (expert), plus Java/C++/Scala exposure.
• ML Frameworks: TensorFlow, PyTorch, JAX, scikit-learn, XGBoost.
• Deployment: Docker, Kubernetes, TensorRT, ONNX, TFLite.
• Cloud: AWS SageMaker, Azure ML, or GCP Vertex AI.
• MLOps: MLflow, WandB, Neptune, etc.
• Data Engineering: Spark, Airflow, Kafka, SQL.
• Version Control: Git, GitHub/GitLab.

Generative AI & LLM Skills

• Strong foundation in Deep Learning, NLP, and Generative AI.
• Hands-on with LLMs: OpenAI, HuggingFace, Anthropic, Cohere, Mistral, LLaMA.
• Experience with agentic workflows using LangGraph, AutoGen, CrewAI, or LangChain Agents.
• RAG experience using LangChain, LlamaIndex, and vector DBs (FAISS, Pinecone, Chroma, Weaviate).
• Understanding of embeddings, vector search, and semantic retrieval.
• Ability to automate workflows, analysis, and summarization using LLMs.

Core Competencies

• Strong ML fundamentals and model performance tuning expertise.
• Solid software engineering and architectural design skills.
• Excellent problem-solving, communication, and documentation abilities.

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