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 [email protected]
#LI-REMOTE
Skills Required
- 8+ years building and shipping production software or data systems
- 3+ years delivering production AI/ML or generative AI solutions to real users
- Experience building production systems with large language models
- Experience with retrieval-augmented generation, agentic workflows, tool use, prompt engineering, and context engineering
- Experience determining when fine-tuning is appropriate
- Strong Python skills
- Experience with modern AI frameworks, orchestration tooling, vector databases, embedding pipelines, and AI service API design
- Experience with version control, testing, and CI/CD
- Production experience with AWS, Azure, or GCP and their AI/ML services
- Familiarity with containerization, infrastructure as code, and deploying and monitoring models at scale
- Experience designing evaluation frameworks for nondeterministic systems
- Working knowledge of data privacy, PII handling, model risk, bias, prompt injection, AI security, and client compliance
- Experience with model selection, inference cost, latency, and performance tradeoffs
- Ability to conduct technical discovery and translate business problems into AI solution designs
- Ability to explain technical tradeoffs to engineers and executives
- Experience mentoring engineers and expanding AI capabilities across a distributed team
- Consulting or client-services experience
- Experience with classical machine learning and the full model lifecycle
- Experience building reusable accelerators or internal assets
Sparq Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Sparq and has not been reviewed or approved by Sparq.
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Leave & Time Off Breadth — PTO with floating holidays and seven U.S. holidays is part of the package, and flexibility around taking time off is highlighted positively. These elements support work–life balance for many roles.
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Retirement Support — A 401(k) program is offered and some postings reference a company match. This provides baseline long‑term savings support even though specific match details are not publicly listed.
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Inclusive Benefits Coverage — Participation in LGBTQ+ inclusion benchmarks and the presence of colleague resource groups signal attention to inclusive policies and benefits. External recognitions further reinforce a focus on equitable workplace practices.
Sparq Insights
What We Do
Sparq is an AI-native digital engineering services firm that re-engineers the systems businesses run on, turning operational bottlenecks into margin, throughput, and decision speed. We work alongside operators, architects, and engineering and business leaders to modernize critical technology, connect fragmented intelligence, and put AI to work where it can have the greatest impact on business performance. Sparq accelerates delivery with proven engineering patterns and production-tested AI components. Everything is validated first in The Shop, Sparq's internal practice that stress-tests new approaches under production-like conditions, then applied through Intelligence Studio, Sparq's applied AI foundation, which embeds them into a client's existing workflows. The result is reduced implementation risk and a shorter time to value. The combination has unlocked more than $90 million in margin for an enterprise mobility client, cut $220 million in operating costs for a leading logistics company, and moved new AI capability from concept to production in under 20 days across multiple engagements.
Why Work With Us
Sparq holds Snowflake Elite Partner, Snowflake CoCo Preferred Partner, and AWS Advanced Tier Services Partner status, serving Fortune 1000 and enterprise clients across transportation & logistics, real estate & construction, and financial services & insurance. Sparq is headquartered in Atlanta, Georgia, with delivery teams across the U.S. & Latam.









