Associate Applied AI Engineer

Summary

Groundswell is a technology integrator and solution provider committed to solving complex challenges facing federal agencies. The Associate Applied AI Engineer will build production-quality software, define requirements with business stakeholders, and develop applications integrating AI capabilities. The role also supports client demonstrations, proofs of concept, internal product development, evaluation, documentation, and client-facing delivery.

Responsibilities

• Take a defined technical approach and build it into production-quality functionality
• Participate in requirements discussions with business stakeholders to understand the workflow, business need, and desired outcome
• Contribute ideas and alternative approaches during solution design, including identifying opportunities to simplify the solution or reduce the AI component where appropriate
• Contribute to building complete applications that integrate AI capabilities with prompt and retrieval design, structured outputs, tool and function definitions, API integration, data handling, error handling, and user-facing functionality
• Build evaluation sets from real data, measure results against them, and report findings accurately, including results that do not support the chosen approach
• Investigate failures by identifying where a capability produced an incorrect result, characterizing the cause, and implementing a fix
• Support client demonstrations and proof-of-concepts to help customers understand how AI can be applied to their business challenges
• Seek feedback, ask thoughtful questions, and continuously build your understanding of client needs and AI best practices
• Instrument and document your work, including logging, traceability, intended behavior, known limitations, validation method, and failure handling
• Move between client delivery, internal product work, rapid proofs of concept, and internal enablement as the work requires
• Raise blockers, unclear requirements, and results you do not trust early rather than working around them
• Contribute reusable patterns, prompts, and evaluation harnesses back to the team

Skills

• Bachelor's degree in a technical field, or equivalent demonstrated ability
• 1+ years of professional software development experience
• Hands-on experience building applications that integrate large language models, including prompt engineering, retrieval-augmented generation, structured extraction, and/or tool use. Experience may be gained through professional work, internships, academic research, or significant personal/open-source projects
• Experience contributing to applications that integrate AI capabilities with APIs, data handling, and user-facing functionality
• Familiarity with a general-purpose language such as Python, TypeScript, or SQL, with experience integrating APIs and working with imperfect data
• Ability to conduct a requirements conversation with a non-technical stakeholder, identify the underlying need, and return with a proposed approach
• Willingness to question a design, including one you have been given, and to make the case for an alternative
• Ability to work through ambiguous requirements with guidance, ask thoughtful questions, and drive assigned work to completion
• Clear written and verbal communication. This role produces documentation and materials that clients read
• Candor about the limits of your knowledge and a willingness to ask rather than assume
• U.S. Citizenship required
• Ability to obtain and maintain any federal government background investigation, suitability determination, or security clearance required by assigned client engagements
• Prior client-facing work in consulting, solutions engineering, professional services, or implementation
• Experience with a low-code or application platform such as Appian, OutSystems, Mendix, Microsoft Power Platform, ServiceNow, or Salesforce
• Public sector or regulated-industry delivery experience
• Experience with cloud AI services such as AWS Bedrock or Azure OpenAI
• Familiarity with LLM evaluation or observability tooling
• Personal or open source projects involving language models, agents, retrieval, or evaluation

Qualifications

Must Haves

• Bachelor's degree in a technical field, or equivalent demonstrated ability
• 1+ years of professional software development experience
• Hands-on experience building applications that integrate large language models, including prompt engineering, retrieval-augmented generation, structured extraction, and/or tool use. Experience may be gained through professional work, internships, academic research, or significant personal/open-source projects
• Experience contributing to applications that integrate AI capabilities with APIs, data handling, and user-facing functionality
• Familiarity with a general-purpose language such as Python, TypeScript, or SQL, with experience integrating APIs and working with imperfect data
• Ability to conduct a requirements conversation with a non-technical stakeholder, identify the underlying need, and return with a proposed approach
• Willingness to question a design, including one you have been given, and to make the case for an alternative
• Ability to work through ambiguous requirements with guidance, ask thoughtful questions, and drive assigned work to completion
• Clear written and verbal communication. This role produces documentation and materials that clients read
• Candor about the limits of your knowledge and a willingness to ask rather than assume
• U.S. Citizenship required
• Ability to obtain and maintain any federal government background investigation, suitability determination, or security clearance required by assigned client engagements

Nice to Haves

• Prior client-facing work in consulting, solutions engineering, professional services, or implementation
• Experience with a low-code or application platform such as Appian, OutSystems, Mendix, Microsoft Power Platform, ServiceNow, or Salesforce
• Public sector or regulated-industry delivery experience
• Experience with cloud AI services such as AWS Bedrock or Azure OpenAI
• Familiarity with LLM evaluation or observability tooling
• Personal or open source projects involving language models, agents, retrieval, or evaluation

Benefits

• 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