Applied AI Engineer

Job not on LinkedIn

🔥 3 minutes ago

🏈 Alabama, Alaska, +44 more states – Remote

🏈 Alabama – Remote 🐻 Alaska – Remote 🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🌺 Hawaii – Remote 🥔 Idaho – Remote 🌽 Illinois – Remote 🌾 Iowa – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote ⚜️ Louisiana – Remote 🦞 Maine – Remote 🦬 Montana – Remote 🌾 Nebraska – Remote 🎰 Nevada – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🌶️ New Mexico – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🌾 North Dakota – Remote 🏈 Ohio – Remote 🌪️ Oklahoma – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote ❄️ Minnesota – Remote 🎸 Mississippi – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🌴 South Carolina – Remote 🗿 South Dakota – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote ⛰️ West Virginia – Remote 🧀 Wisconsin – Remote 🦬 Wyoming – Remote

💵 $88.2k - $171.6k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 0%

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Groundswell

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📦 Logistics

🎖️ Defense

Consulting • Logistics • Defense

Groundswell is a leading technology partner for federal agencies, specializing in delivering innovative solutions for modernization and efficiency. With expertise in platforms like Appian, SAP, Workday, and UiPath, Groundswell focuses on empowering federal agencies with low-code development, advanced ERP, and automation technologies. The company partners with federal organizations to enhance recruitment strategies, manage defense transportation, and optimize project management. Groundswell's mission is to challenge the traditional government contracting approach by offering cutting-edge, agile, and tailored technology solutions to help federal agencies meet their goals.

📋 Description

• Define business and technical requirements and the technical approach for AI capabilities • Own capabilities end to end, including discovery, design, development, validation, deployment, and operation • Work across client delivery, internal product development, rapid proofs of concept, and internal enablement • Select appropriate AI patterns such as extraction, classification, summarization, retrieval, or agentic workflows • Recommend simpler non-AI solutions when appropriate • Define measurable success criteria, accuracy targets, human review thresholds, acceptance conditions, and failure definitions • Build complete capabilities including prompt and retrieval design, structured outputs, tool and function definitions, API integration, data handling, error states, and user interfaces • Build evaluation sets from real data, measure results, iterate, and determine deployment readiness • Make architecture decisions considering quality, cost, latency, security, and authorization constraints • Operationalize capabilities with governance, logging, traceability, monitoring, and post-launch optimization • Help clients understand possibilities, anticipate needs, shape future work, and build proofs of concept • Mentor engineers new to AI through code review, pairing, and guidance • Maintain current knowledge of models, tooling, and techniques and develop reusable patterns • Produce documentation covering solution behavior, limitations, validation, and incorrect-result handling

🎯 Requirements

• 4+ years building and shipping production software • At least 1 year 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 ability to own a capability end to end, from an ambiguous requirement through to something in production that people rely on • 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, applied across the full application rather than the AI layer alone • Proven ability to lead requirements conversations with non-technical stakeholders and translate what you hear into a technical approach • Sound judgment on tradeoffs between accuracy, cost, latency, and complexity, with the ability to explain those tradeoffs to both engineers and executives • Excellent written communication • Ability to work independently through ambiguous requirements, define an appropriate technical approach, and drive work through implementation and delivery with minimal direction • Willingness to teach • U.S. Citizenship required • Ability to obtain and maintain any federal government background investigation, suitability determination, or security clearance required by assigned client engagements • Master’s degree in a relevant field such as Data Science, Business Analytics, Mathematics, or Computer Science (preferred) • Experience with a low-code or application platform such as Appian, OutSystems, Mendix, Microsoft Power Platform, ServiceNow, or Salesforce (preferred) • Public sector or regulated-industry delivery experience, including compliance and authorization processes (preferred) • Experience with cloud AI services such as AWS Bedrock or Azure OpenAI (preferred) • Familiarity with LLM evaluation or observability tooling (preferred) • Prior consulting, solutions engineering, professional services, or embedded client work (preferred)

🏖️ 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