Senior Applied AI Engineer

Groundswell

. Lead discovery with business and technical stakeholders to understand workflows, supported decisions, and acceptable results .

Posted 9/21/2026full-timeRemote • United StatesSenior💰 $149,748 - $205,305 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping production software with a focus on AI-enabled capabilities, including prompt engineering and integration of large language models. Proven ability to lead technical discussions, mentor engineers, and operationalize solutions in client environments while ensuring quality and compliance.

Highest-signal resume keywords

AI System Quality EvaluationLarge Language Model IntegrationProgramming in Python, TypeScript, or SQLAPI Integration and Data HandlingClient Stakeholder Engagement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Production Software DevelopmentPrompt EngineeringStructured ExtractionTool UseAgent PatternsTest Set BuildingMetric DefinitionDeployment Decision MakingGovernance and TraceabilityError State Management

Soft Skills

Excellent Written CommunicationSound JudgmentAbility to Work IndependentlyMentoring EngineersTranslating Technical Approaches

Tools & Technologies

AWS BedrockAzure OpenAIAppianOutSystemsMendixMicrosoft Power PlatformServiceNowSalesforce

Certifications & Qualifications

U.S CitizenshipFederal Government Background Investigation

Industry Keywords

Public Sector DeliveryRegulated Industry ExperienceConsultingSolutions EngineeringProfessional Services

Tech Stack

Tools & technologies

AWSAzurePythonServiceNowSQLTypeScript

About the role

Key responsibilities & impact

Lead discovery with business and technical stakeholders to understand workflows, supported decisions, and acceptable results
Define measurable success criteria, including accuracy targets, human review thresholds, acceptance conditions, and failure definitions
Recommend non-AI solutions when rules, process changes, or improved interfaces are more appropriate
Select appropriate AI patterns such as extraction, classification, summarization, retrieval, or agentic workflows
Make and defend architecture decisions considering quality, cost, latency, security, and authorization
Build complete AI-enabled capabilities, including prompt and retrieval design, structured outputs, tools, APIs, data handling, error states, and user interfaces
Build evaluation sets from real data and iterate based on results
Determine deployment readiness
Operationalize capabilities in client environments with governance, logging, and traceability
Produce documentation covering solution behavior, limitations, validation, and incorrect-result handling
Monitor and optimize quality, cost, latency, and drift after launch
Shape client roadmaps and demonstrate possibilities through working proofs
Mentor engineers newer to AI and review their work
Contribute reusable patterns to the team
Move between client delivery, internal product work, rapid proofs of concept, and internal enablement

Requirements

What you’ll need

7+ years building and shipping production software
At least 2 years of hands-on experience building applications that integrate large language models, including prompt engineering, retrieval-augmented generation, structured extraction, tool use, and agent patterns
Demonstrated experience evaluating AI system quality, including building test sets, defining metrics, and making deployment decisions based on evidence
Strong programming ability in a general-purpose language such as Python, TypeScript, or SQL
Experience integrating APIs and working with imperfect data across the full application
Proven ability to lead requirements conversations with non-technical stakeholders and translate them into a technical approach
Sound judgment on tradeoffs between accuracy, cost, latency, and complexity
Excellent written communication
Ability to work with minimal direction in ambiguous situations
Track record of improving the capability of other engineers
U.S Citizenship required
Ability to obtain and maintain any federal government background investigation, suitability determination, or security clearance required by assigned client engagements
Preferred: Master’s degree in a relevant field
Preferred: Experience with low-code or application platforms such as Appian, OutSystems, Mendix, Microsoft Power Platform, ServiceNow, or Salesforce
Preferred: Public sector or regulated-industry delivery experience
Preferred: Experience with AWS Bedrock or Azure OpenAI
Preferred: Familiarity with LLM evaluation or observability tooling
Preferred: Prior consulting, solutions engineering, professional services, or embedded client work

Benefits

Comp & perks

Comprehensive medical, dental, and vision plans
Flexible Spending Account
4% 401K Match (immediate vesting)
Paid Time Off
Tuition reimbursement, certification programs, and professional development
Flexible work schedule
On-site gym and childcare option