Senior AI Engineer - Production Solutions & Client Delivery

Groundswell

Michigan

On-site

USD 150,000 - 205,000

Full time

3 days ago
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Benefits offered by this job

Medical, dental, vision plans
401K match
Paid time off
Tuition reimbursement and professional
Flexible work schedule
On-site gym and childcare

Job summary

Groundswell is seeking an AI solutions engineer to transform ambiguous business problems into practical AI-enabled workflows. This client-facing, hands-on role requires coordinating with stakeholders to decide when AI adds value, designing the approach, building it, and maintaining production-ready systems across discovery, build, and operations.

You will work across client delivery, internal product development, rapid proofs of concept, and internal enablement, communicating clearly with

Qualifications

  • Must have 7+ years building and shipping production software.
  • At least 2 years hands-on experience building apps that integrate large language models, including prompt engineering, retrieval-augmented generation, structured extraction, tool use, and agent patterns.
  • Experience evaluating AI system quality: building test sets, defining metrics, deployment decisions based on evidence.
  • Strong programming ability in Python, TypeScript, or SQL, with API integration and working with imperfect data across the full app, not just the AI layer.
  • Proven ability to lead requirements conversations with non-technical stakeholders and translate feedback into a technical approach.
  • Sound judgment on tradeoffs between accuracy, cost, latency, and complexity, with ability to explain to engineers and executives.
  • Excellent written communication; produces client-facing docs and design rationale.
  • Ability to work with minimal direction in ambiguous situations, surface problems, propose approaches, and drive to a decision.
  • Track record of improving other engineers' capabilities, US Citizenship required; ability to obtain/maintain federal background checks.

Responsibilities

  • Lead discovery with business and technical stakeholders to understand the workflow, decision, and acceptance criteria.
  • Define measurable success criteria before building: accuracy targets, human review thresholds, acceptance conditions, failure definition.
  • Recommend against AI when a simpler solution suffices; propose rules, process changes, or better interfaces.
  • Select the AI pattern appropriate to the problem (extraction, classification, summarization, retrieval, or agentic workflow).
  • Make and defend architecture decisions on where workloads run, balancing quality, cost, latency, security, and authorization.
  • Build the complete capability: prompt design, retrieval, structured outputs, API integration, data handling, error states, and UI.
  • Create evaluation sets from real data; iterate based on results, not intuition.
  • Determine production readiness of a capability; identify when not ready.
  • Operationalize capabilities with governance, logging, and traceability in client environments.
  • Produce documentation detailing capabilities, limitations, validation, and handling of incorrect results.
  • Monitor quality, cost, latency, and drift post-launch; optimize as better options arise.
  • Set direction for clients by illustrating what's possible with working proofs; support roadmap with working outcomes.
  • Mentor engineers to raise technical capability; review work and build team judgment.
  • Contribute reusable patterns to prevent starting from scratch on each project.
  • Move between client delivery, internal product work, rapid PoCs, and enablement as needed.

Job description

Groundswell is seeking an AI solutions engineer to transform ambiguous business problems into practical AI-enabled workflows. This client-facing, hands-on role requires coordinating with stakeholders to decide when AI adds value, designing the approach, building it, and maintaining production-ready systems across discovery, build, and operations.

You will work across client delivery, internal product development, rapid proofs of concept, and internal enablement, communicating clearly with

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