Senior AI/ML Engineer

Modus Create

2h•Remote

About The Position

We’re looking for an exceptional Senior AI Engineer with 4+ years of software engineering experience and a proven track record delivering Generative AI solutions to join Modus’s Engineering Consulting team. What You’ll Do No two days look the same in this role. You might spend one day whiteboarding an architecture with a client, the next drafting a proposal for a new engagement, and the next deep in code shipping an LLM-powered feature. As a senior engineer on our consulting team, you'll move fluidly between: Designing and building AI solutions: scoping, architecting, and implementing applications powered by generative AI, from proof of concept to production deployment. Working directly with clients: understanding their problems, proposing solutions, and translating business needs into technical plans. You're the trusted technical advisor in the room. Hands-on engineering: writing production-quality code, integrating LLMs and ML models into real systems, and deploying them to the cloud. Collaborating across disciplines: partnering with cloud architects, DevOps specialists, and front-end developers to deliver end-to-end solutions. Supporting business development — contributing to proposals, scoping engagements, and supporting sales and marketing efforts when needed. About You You're an engineer who thrives in client-facing environments and can own problems end-to-end, from a vague business need to a working system in production. Your core strength is deploying and operationalizing AI. You have hands-on experience deploying large and small language models (LLMs/SLMs) in the cloud and on-premises, and you're comfortable with techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and agentic architectures (tool use, multi-agent orchestration, human-in-the-loop workflows). You understand how to evaluate model outputs and build reliable systems around inherently probabilistic components. Familiarity with classical ML (prediction, classification) and data science fundamentals is a desirable plus. A background in cloud services for machine learning, text extraction, speech recognition, or computer vision will broaden the engagements you can contribute to. Proficiency in Python is a must. Experience with other programming languages like Java, Scala, Rust or R is highly desirable, as it will enable you to work on a broader range of engagements. You’ll work side by side with cloud architects, DevOps specialists and front-end developers, so some knowledge and experience in any of these would help in collaboration. You should be comfortable presenting work to both technical and non-technical audiences, driving alignment with stakeholders and between technical and business outcomes, leading technical teams and cross-collaborating with teams in adjacent domains. Experience in supporting sales and marketing efforts is a desirable plus.

Requirements

LLM deployment and agentic AI: experience with LLM orchestration frameworks (e.g., LangChain, LangGraph, Google ADK), agent tooling and protocols (e.g., MCP, function calling), and evaluation/observability libraries. Cloud deployment of LLM-based applications
Cloud AI services: experience with managed AI services such as Amazon Bedrock, SageMaker, Rekognition, etc. or equivalents on other platforms
Machine learning frameworks: familiarity with frameworks like TensorFlow or PyTorch is a plus
AI-assisted development tools: experience with AI-powered coding assistants (e.g., GitHub Copilot, Cursor, Claude Code) and agentic coding workflows
Cloud platforms: solid experience with at least one major cloud provider (AWS preferred); infrastructure as code (e.g., Terraform) is a plus
Version control and DevOps: Git, GitHub/GitLab; DevOps and CI/CD experience is a big plus
Programming and scripting languages: Python, Bash; knowledge of other languages is a plus
Data storage and querying: SQL and NoSQL databases
Above all, AI is a rapidly-evolving field so the curiosity and drive to keep learning matter as much as what you already know.

Nice To Haves

Familiarity with classical ML (prediction, classification) and data science fundamentals is a desirable plus.
A background in cloud services for machine learning, text extraction, speech recognition, or computer vision will broaden the engagements you can contribute to.
Experience with other programming languages like Java, Scala, Rust or R is highly desirable, as it will enable you to work on a broader range of engagements.
Experience in supporting sales and marketing efforts is a desirable plus.

Responsibilities

Designing and building AI solutions: scoping, architecting, and implementing applications powered by generative AI, from proof of concept to production deployment.
Working directly with clients: understanding their problems, proposing solutions, and translating business needs into technical plans. You're the trusted technical advisor in the room.
Hands-on engineering: writing production-quality code, integrating LLMs and ML models into real systems, and deploying them to the cloud.
Collaborating across disciplines: partnering with cloud architects, DevOps specialists, and front-end developers to deliver end-to-end solutions.
Supporting business development — contributing to proposals, scoping engagements, and supporting sales and marketing efforts when needed.