Duration : 6 Months to start (high possibility of extension)
Location : Remote (EST Hours Preferred)
Our client is in the early stages of building enterprise AI capabilities and is seeking a Senior AI Engineer / Applied AI Specialist to help design, develop, and scale initial AI and machine learning use cases.
This role is highly hands-on and exploratory. The successful consultant will act as a technical SME, supporting model development, AI agent experimentation, and architectural decision-making while helping guide the team toward a scalable, future-ready AI approach.
The environment is green, making this an ideal role for someone who enjoys shaping direction, working through ambiguity, and building from first principles.
Key Responsibilities
- Design, build, and deploy AI and ML use cases aligned to business needs
- Develop and evaluate machine learning models, including experimentation and iteration
- Support early-stage AI agent development and GenAI use cases
- Provide technical guidance on AI architecture, tooling, and best practices
- Collaborate with data engineering and platform teams to ensure AI solutions are production-ready
- Advise on the selection and use of AI services and platforms as the tech stack evolves
- Help establish foundational AI development standards, patterns, and workflows
- Mentor and support team members through knowledge sharing and technical leadership
- Balance hands-on delivery with advisory input as the AI capability matures
- Architect workflows, eliminate operational inefficiencies, and rapidly ship automations that unlock leverage across every function.
- Stay updated with the latest in LLMs, agent orchestration frameworks, and AI tooling
Must-Have Requirements
Experience building and shipping Agentic AI / LLM-driven tools & productsBuild scalable APIs for model access, integration, and service orchestrationProficiency in RAG architectures, including vector stores (e.g., Pinecone, Weaviate), embedding models, and retrieval tuningHands-on development experience in n8n and complementary no-code / low-code tooling.Senior-level experience in AI / Machine Learning / Data ScienceStrong background in model development, training, and evaluationExperience building applied AI solutions in real-world environmentsHands-on experience with AWS AI / ML services, such as :SageMakerBedrockOther AWS-native AI servicesStrong Python experience and familiarity with common ML frameworksAbility to operate effectively in ambiguous, early-stage environmentsStrong communication skills and ability to influence without direct authorityComfortable acting as both builder and advisor