Artificial Intelligence (AI) Engineer

Description

AI Lead Engineer

Skills:

Proactive self-starter with excellent interpersonal, communication, and customer service skills.

Expert-level AI/ML and full-stack development skills, with strong hands-on experience building and integrating backend services and frontend applications using modern frameworks such as Node.js and React. Strong emphasis on clean, maintainable, reproducible, well-tested, and well-documented code.

Ability to manage multiple tasks and projects simultaneously.

Collaborative team player with a focus on achieving common goals.

Meticulous attention to detail.

Quick learner with a passion for staying current with emerging technologies and industry trends.

Requirements

Required Experience:

Deep expertise in RAG systems, LLMs, embeddings, vector databases, and AI infrastructure

Experience designing semantic retrieval and knowledge platforms, including curated corpora and grounding/citation patterns (e.g., "show your sources" for internal auditability)

Experience evaluating AI models for different tasks

Strong ability and experience to leverage cloud infrastructure

Experience with data quality and metadata management (data lineage, dataset versioning, business glossary/taxonomy) and implementing automated quality checks and anomaly detection

Experience implementing secure GenAI platform controls, including prompt logging, red-teaming, content filtering/leakage prevention, and model access controls/tenant isolation

Excellent collaboration skills and ability to work with non-technical stakeholders

Proven ability to work in existing codebases, improve reliability, performance, and readability over time.

5+ years of hands-on experience in machine learning engineering, with significant work developing and maintaining AI systems in production.

Strong software engineering practices including modular design, refactoring, and technical debt management; unit, integration, and regression testing; as well as code reviews and shared coding standards

Strong expertise in machine learning fundamentals and statistical modeling, including, but not limited to:

o Supervised, unsupervised, and reinforcement learning

o Model evaluation, bias, overfitting, and error analysis

o Probabilistic and statistical reasoning

Proficiency in Python and major ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, HuggingeFace, LangChain, LlamaIndex).

Hands-on experience with cloud-based ML platforms (AWS SageMaker, Azure ML, or Google AI Platform).

Technology Doesn't Change the World, People Do.

Robert Half is the world's first and largest specialized talent solutions firm that connects highly qualified job seekers to opportunities at great companies. We offer contract, temporary and permanent placement solutions for finance and accounting, technology, marketing and creative, legal, and administrative and customer support roles.

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