Note: The job is a remote job and is open to candidates in USA. Sparq is a modern product engineering partner that helps organizations modernize confidently in the age of AI. The Principal AI Engineer will design and build production AI systems, implement AI solutions on cloud platforms, and serve as a senior technical voice in client conversations.
Responsibilities
- 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
Skills
- 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
- 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
- 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
- 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
- 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
- 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
- Practical judgment on model selection, inference cost, and latency tradeoffs, including recognizing when a smaller model or a non-AI solution is the right answer
- Able to run technical discovery with client stakeholders, translate business problems into AI solution designs, and explain tradeoffs credibly to both engineers and executives
- Comfortable supporting pre-sales and solutioning conversations
- Experience mentoring engineers and raising AI capability across a team, including geographically distributed teams
- Self-motivated, flexible, and reliable in delivering on time, with the ability to work in a fast-paced, highly entrepreneurial environment
- Consulting or client-services experience is a strong plus
- Experience building reusable accelerators or internal assets is a plus
Benefits
- Ongoing investment in your growth through training, mentorship, and industry certifications
- Recognition programs and employee awards within an inclusive culture that celebrates great work, including our AI Innovators Program
- Remote or hybrid work options
- Robust benefits package
- Matching 401(k) plan
- Substantial PTO
- Tuition reimbursement
Company Overview