Job description

LMI is seeking a Software Developer, Applications/AI Automation Engineer to build automation, AI-enabled applications, prototypes, integrations, APIs, and production-ready software components for Department of Veterans Affairs (VA) modernization initiatives. The role spans no-code, low-code, and full-code delivery and favors approved reusable patterns before custom development. This position follows a hybrid work model, with an expectation of approximately 25% onsite presence at LMI’s Tysons headquarters or Washington, DC. This is a builder role for an engineer who can move from rough problem statements to working technical increments quickly without sacrificing maintainability. The engineer should be comfortable deciding when configuration or low-code is sufficient, when custom code is justified, and how to evolve an early prototype into a supportable enterprise solution. The successful candidate will bring modern software-engineering discipline to automation and AI-enabled work. That includes secure coding, testability, version control, API design, logging, documentation, code review, and careful handling of prompts, model integrations, data flows, and other components that can introduce new failure modes. The engineer should take ownership of the full technical lifecycle, not just initial build tasks. Strong candidates will be curious about how a solution behaves with real data and users, responsive to defects and feedback, and disciplined about leaving behind code, configuration, documentation, and tests that another engineer can understand. The ideal candidate is a pragmatic builder who can move quickly from validated workflow needs to testable solutions, troubleshoot across system boundaries, and package reusable code and configuration for future use. LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed. Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value. • Build workflow automations, lightweight applications, prototypes, integrations, and production-quality components. • Select the simplest approved implementation approach across no-code, low-code, and full-code options. • Develop and troubleshoot APIs, scripts, services, prompts, agents, automation logic, and application components. • Support technical feasibility testing, prototype evaluation, pilot readiness, implementation, and handoff. • Apply secure coding, version control, testing, code review, documentation, and configuration-management practices. • Partner with HCD/UX, data, architecture, security, platform, QA, and business stakeholders to fit real workflows. • Package reusable code, prompts, configurations, integration patterns, and technical guidance. • Resolve issues that cross application, data, integration, automation, or platform boundaries. • Translate validated user and workflow needs into technical designs, implementation tasks, acceptance criteria, and working software across low-code, automation, API, and full-code approaches. • Implement defensive error handling, logging, configuration management, secrets handling, automated tests, and observability appropriate to the maturity and risk of each solution. • Evaluate and integrate AI/LLM capabilities where justified, including prompt orchestration, retrieval, structured outputs, tool/API calls, evaluation logic, and guardrails within approved environments. • Participate actively in peer review, technical troubleshooting, refactoring, and knowledge transfer so solutions can be maintained by the broader engineering team rather than a single developer. • Use technical spikes and feasibility tests to reduce uncertainty around APIs, data access, model behavior, platform limits, integration constraints, performance, and security before committing to a larger build. • Profile and improve reliability, latency, cost, maintainability, and user-facing behavior as solutions mature, using evidence from testing and operational feedback rather than relying on prototype assumptions. • Bachelor's degree in computer science, software engineering, information systems, engineering, or a related field; equivalent experience may be considered. • 7+ years in application development, automation engineering, systems integration, prototyping, or related software delivery. • Strong coding in Python, JavaScript/TypeScript, C#, Java, or comparable languages plus hands-on API and integration experience. • Experience choosing among no-code, low-code, and full-code approaches based on complexity, security, maintainability, and enterprise constraints. • Recommended certification: cloud developer, Microsoft Power Platform Developer, DevOps, or comparable software-engineering credential. • Ability to satisfy VA personnel vetting and applicable security, privacy, records, and data-handling requirements. • Demonstrated experience delivering production-quality software or automation through a modern SDLC, including code review, branching, testing, release discipline, documentation, and defect resolution. • Strong understanding of API design, authentication/authorization, data interchange, integration patterns, secure coding, and troubleshooting across application and service boundaries. • Ability to evaluate tradeoffs among custom development, configuration, scripting, low-code, and managed services based on complexity, security, supportability, performance, and lifecycle cost. • Strong debugging ability across application code, APIs, data transformations, authentication, configuration, network/service dependencies, and third-party or managed services. • Experience estimating engineering work, decomposing requirements into implementable increments, and communicating technical risk or tradeoffs clearly to non-engineering stakeholders. Desired Qualifications • 9+ years delivering enterprise applications, automation, integrations, or AI-enabled solutions in federal or regulated environments. • Experience with generative AI/LLMs, agentic workflows, Azure AI services, Power Platform, Azure Functions, Logic Apps, or comparable tooling. • Experience with CI/CD, containers, infrastructure integration, observability, and production support. • Additional cloud AI, security, DevSecOps , or advanced developer certification is preferred. • Hands-on experience evaluating or implementing generative-AI application patterns, retrieval-augmented generation, agent/tool workflows, prompt evaluation, or model-service integration is preferred. • Microsoft Azure AI Engineer, Power Platform Developer, cloud developer, software engineering, or DevSecOps certifications are valuable when supported by strong practical engineering experience. • Experience with Azure Functions, Logic Apps, Microsoft 365/Power Platform integration, containerized services, or comparable enterprise automation technologies is helpful. • A portfolio of reusable libraries, internal tools, open-source contributions, technical prototypes, or documented engineering patterns can strengthen a candidate's qualifications. Target salary range: $140,000-$170,000 Disclaimer: The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances. #LI-SH1 US-VA-Tysons US-DC-Washington, DC We can recommend jobs specifically for you! Click here to get started.

Requirements

Must-haves

This position follows a hybrid work model, with an expectation of approximately 25% onsite presence at LMI’s Tysons headquarters or Washington, DC.
The ideal candidate is a pragmatic builder who can move quickly from validated workflow needs to testable solutions, troubleshoot across system boundaries, and package reusable code and configuration for future use.
Build workflow automations, lightweight applications, prototypes, integrations, and production-quality components.
Select the simplest approved implementation approach across no-code, low-code, and full-code options.
Develop and troubleshoot APIs, scripts, services, prompts, agents, automation logic, and application components.
Support technical feasibility testing, prototype evaluation, pilot readiness, implementation, and handoff.
Apply secure coding, version control, testing, code review, documentation, and configuration-management practices.
Partner with HCD/UX, data, architecture, security, platform, QA, and business stakeholders to fit real workflows.
Package reusable code, prompts, configurations, integration patterns, and technical guidance.
Resolve issues that cross application, data, integration, automation, or platform boundaries.
Translate validated user and workflow needs into technical designs, implementation tasks, acceptance criteria, and working software across low-code, automation, API, and full-code approaches.
Implement defensive error handling, logging, configuration management, secrets handling, automated tests, and observability appropriate to the maturity and risk of each solution.
Evaluate and integrate AI/LLM capabilities where justified, including prompt orchestration, retrieval, structured outputs, tool/API calls, evaluation logic, and guardrails within approved environments.
Participate actively in peer review, technical troubleshooting, refactoring, and knowledge transfer so solutions can be maintained by the broader engineering team rather than a single developer.
Use technical spikes and feasibility tests to reduce uncertainty around APIs, data access, model behavior, platform limits, integration constraints, performance, and security before committing to a larger build.
Profile and improve reliability, latency, cost, maintainability, and user-facing behavior as solutions mature, using evidence from testing and operational feedback rather than relying on prototype assumptions.
Bachelor's degree in computer science, software engineering, information systems, engineering, or a related field; equivalent experience may be considered.

Nice-to-haves

Experience with generative AI/LLMs, agentic workflows, Azure AI services, Power Platform, Azure Functions, Logic Apps, or comparable tooling.
Experience with CI/CD, containers, infrastructure integration, observability, and production support.
Additional cloud AI, security, DevSecOps , or advanced developer certification is preferred.
Hands-on experience evaluating or implementing generative-AI application patterns, retrieval-augmented generation, agent/tool workflows, prompt evaluation, or model-service integration is preferred.
Microsoft Azure AI Engineer, Power Platform Developer, cloud developer, software engineering, or DevSecOps certifications are valuable when supported by strong practical engineering experience.
Experience with Azure Functions, Logic Apps, Microsoft 365/Power Platform integration, containerized services, or comparable enterprise automation technologies is helpful.
A portfolio of reusable libraries, internal tools, open-source contributions, technical prototypes, or documented engineering patterns can strengthen a candidate's qualifications.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapillmpythonjavascripttypescriptjavaazureci/cd

Platform: icims
Effort: medium