AI EngineerOteemo Inc. • Richmond, VA, United States

AI Engineer

Oteemo Inc. • Richmond, VA, United States

[job_card.variable_hours_ago]

[job_preview.job_type]

[job_card.full_time]

[job_card.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
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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