Principal AI Engineer
At Sparq , we help companies solve the right problems—not just build more technology.
We’re a modern product engineering partner blending strategy, craftsmanship, and speed to help organizations modernize confidently in the age of AI. From data ecosystems to digital products and AI acceleration, we turn complexity into clarity and ideas into impact.
If you’re driven to build what’s next, lead with empathy, and deliver excellence without ego, you’ll feel right at home at Sparq .
C2C is not available
Must be authorized to work in the U.S. without sponsorship
Why you will enjoy Mondays again:
- Opportunity to work alongside a talented, diverse team in a collaborative and creative environment
- Ongoing investment in your growth through training, mentorship, and industry certifications
- Hands-on exposure to cutting-edge technologies across multiple industries
- Recognition programs and employee awards within an inclusive culture that celebrates great work, including our AI Innovators Program
- Remote or hybrid work options
- Competitive salary + bonus opportunities
- Robust benefits package, matching 401(k) plan, and substantial PTO
- Tuition reimbursement
A Day in the Life:
- Design and build production AI systems for client environments, including retrieval-augmented generation pipelines, agentic workflows, and model integration, applying fine-tuning where it is genuinely warranted.
- Implement and deploy AI solutions on cloud platforms, ensuring scalability, reliability, and performance.
- Use Python for data preprocessing, model development, and automation of AI workflows.
- Define and build evaluation frameworks so we can prove solution quality to clients rather than demonstrate it anecdotally.
- Serve as the senior technical voice in client conversations, from discovery through delivery, and mentor engineers across accounts.
- Collaborate with the development team to broaden AI capabilities and enhance existing solutions.
- Research and experiment with emerging AI technologies, staying ahead of industry advancements and bringing practical recommendations back to the team.
- Optimize and monitor AI systems post-deployment, ensuring efficiency, accuracy, cost control, and reliability.
- Actively use AI tools, including Claude through our Anthropic partnership, to streamline tasks, improve the quality of your work, and share best practices with teammates while continuously seeking new ways to integrate AI into your everyday workflows
What it takes:
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Experience: 8+ years building and shipping production software or data systems, with 3+ years specifically delivering AI/ML or generative AI solutions that reached real users. Consulting or client-services experience is a strong plus.
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Hands-on AI/ML: Demonstrated experience building production systems with large language models, including retrieval-augmented generation, agentic workflows and tool use, prompt and context engineering, and the judgment to know when fine-tuning is and is not the right call. Experience with classical ML and the full model lifecycle is valued.
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Engineering: Strong Python. Experience with modern AI frameworks and orchestration tooling, vector databases and embedding pipelines, and API design for AI-backed services. Comfortable with version control, testing, and CI/CD.
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Cloud & MLOps: Production experience on AWS, Azure, or GCP, including their AI/ML services. Familiarity with containerization, infrastructure as code, and deploying and monitoring models at scale.
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Evaluation & Quality: Experience designing evaluation frameworks for nondeterministic systems. Able to define accuracy, latency, and cost targets and prove a system meets them both before and after it ships.
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Responsible AI & Security: Working knowledge of data privacy and PII handling, model risk and bias, prompt injection and other AI-specific attack surfaces, and how to satisfy client compliance requirements.
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Cost & Performance: Pr