About the Role
We're looking for a Senior AI Engineer who doesn't just work with AI, they think in it. This is a role for someone who has internalized AI-first development patterns, builds with LLMs as a primary primitive, and can architect systems that put intelligent automation at the core rather than the edge.
What You'll Do
Design and build production-grade AI systems including LLM-powered pipelines, agentic workflows, and retrieval-augmented generation (RAG) architectures
Lead the integration of AI capabilities across products, from prototyping through to scalable deployment
Evaluate, fine-tune, and optimize foundation models for specific use cases; stay current on the rapidly evolving model landscape
Define engineering best practices for prompt engineering, model evaluation, observability, and safety guardrails
Collaborate with product and platform teams to identify high-leverage AI opportunities
Mentor engineers on AI-native development patterns and help level up the broader team
What We're Looking For
5+ years of software engineering experience, with at least 2 years focused on applied AI/ML systems
Deep hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and orchestration frameworks such as LangChain, LlamaIndex, or similar
Strong programming skills in Python, TypeScript, or equivalent, we care more about engineering fundamentals than language loyalty
Experience with vector databases (Pinecone, Weaviate, pgvector), embeddings, and semantic search
Proven ability to ship AI features to production, not just demos or notebooks
Comfort operating in ambiguity: you can take a vague idea and turn it into a scoped, working system
Experience with evaluation frameworks, A/B testing for model outputs, and monitoring for model drift or degradation
Nice to Have
Experience with fine-tuning or RLHF workflows
Familiarity with multi-agent architectures and tool-use patterns
Background in ML engineering (training pipelines, model serving, MLOps)
Contributions to open-source AI projects
What "AI-Native" Means to Us
This isn't a traditional ML role retrofitted with a trendy title. We mean someone for whom AI is the default lens, who reaches for an LLM-based solution where others would reach for a rule engine, who understands the tradeoffs between prompt engineering and fine-tuning, and who builds systems that stay useful as the underlying models evolve.
Skills Required
- 5+ years of software engineering experience with at least 2 years focused on applied AI/ML systems.
- Hands-on experience with LLM APIs such as OpenAI, Anthropic, Gemini and orchestration frameworks like LangChain or LlamaIndex.
- Strong programming skills in Python or TypeScript.
- Experience with vector databases (Pinecone, Weaviate, pgvector), embeddings, and semantic search.
- Proven ability to ship AI features to production (not just prototypes or notebooks).
- Experience with evaluation frameworks, A/B testing for model outputs, and monitoring for model drift or degradation.
- Comfort operating in ambiguity and scoping vague ideas into working systems.
- Experience with fine-tuning or RLHF workflows.
- Familiarity with multi-agent architectures and tool-use patterns.
- Background in ML engineering (training pipelines, model serving, MLOps).
- Contributions to open-source AI projects.
What We Do
Mavric is a full-service digital agency and software development firm that provides CTO-led development services. They specialize in strategy, user experience design, and digital transformation, helping visionary founders create 'Most Lovable Products' (MLPs) through a transparent and collaborative approach known as The Mavric Method, focusing on creating scalable and high-impact digital solutions across various industries.
