Skip to content

Principal AI Engineer

Published · Updated

Pay not postedUSRemotePrincipal

This principal-level engineer builds and deploys production AI systems for client environments, spanning generative AI workflows, cloud implementation, evaluation, and post-deployment optimization.

Find roles that fit you

We find roles for your experience and goals, explain the fit, and help you get introduced to hiring teams.

We never share your profile with employers without your permission.

Try NextmoveCreate an account, then add your resume
View posting at Sparq

At a glance

Posted base pay

Not posted

The work

Builds what the customer runs

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales
  2. Proof of concept (not covered)
  3. Implementation
  4. Operations
Coding
Writes production code
Builds for
External customers
Level
Staff+
Role
Technical lead

What they ask for

Experience

  • 8+ yearsbuilding and shipping production software or data systems
  • 3+ yearsdelivering AI/ML or generative AI solutions that reached real users

Background

  • Software engineering
  • Implementation and data engineering

Tools

  • Python
  • large language models
  • retrieval-augmented generation
  • agentic workflows
  • Claude
  • vector databases
  • AWS
  • Azure
  • GCP
  • CI/CD

Visa

  • No visa sponsorship

Less common in FDE jobs

  • Responsibility level: Staff+17%
  • Company size: About 201–1,000 people18%
  • Covers pre-sales25%
  • Fully remote29%

Share of US FDE postings that state each fact.

The job description from Sparq

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
  • 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

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Cost & Performance: 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.
  • Client-Facing Skills: 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.
  • Leadership: Experience mentoring engineers and raising AI capability across a team, including geographically distributed teams. Experience building reusable accelerators or internal assets is a plus.
  • Adaptability: Self-motivated, flexible, and reliable in delivering on time, with the ability to work in a fast-paced, highly entrepreneurial environment.

Regardless of your specific role, we seek individuals who are excited to explore, adopt, and evangelize AI tools and methodologies. If you have experience in AI or a proven track record of rapidly learning and mentoring others on emerging tech, you’ll fit right in.

Equal Employment Opportunity Policy: Sparq is proud to offer equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic.

We are committed to providing equal employment opportunities and believe in an inclusive workplace. If you require reasonable accommodations to participate in the job application or interview process, please let us know by contacting recruiting@teamsparq.com

#LI-REMOTE

View posting at Sparq

About Sparq

Sparq modernizes enterprise systems and delivers AI, data, and software engineering solutions for operational workflows.

Private Late · 500–1000 people

Similar jobs

Hiring at Sparq and want this page changed or removed? Email info@nextmove.md and we take it down.

Pay and conditions

Posted pay
Pay not posted
Location
US
Work arrangement
Remote
Remote work restrictions
Remote or hybrid work options; United States
Visa sponsorship
Not available
Experience requirements
  • 8+ years: building and shipping production software or data systems (required)
  • 3+ years: delivering AI/ML or generative AI solutions that reached real users (required)