Job Description

Focus: Application Support, Defect Resolution & AI Model Optimization

Employment Type: Full-Time

Location: United States – Remote

Experience Level: Mid-Level

Security Requirement: Must be a U.S. Citizen and eligible to obtain and maintain the required Public Trust determination and DoD system access.

About the Role

We are seeking a Mid-Level Software Engineer / Application Developer to support the stability, maintenance, security, and continuous improvement of an AI-enabled software platform built on TypeScript, Node.js, and AWS, operating within a federal/DoD technology environment.

The primary responsibility of this role is to investigate and resolve application defects, system issues, and technical problems identified through autonomous testing, human validation, monitoring, or user feedback.

The engineer will also perform AI model tuning and optimization, analyzing system performance and AI behavior and implementing controlled improvements to prompts, configurations, model interactions, workflows, and related application components.

You may be required to work in a government-managed AWS environment, where infrastructure, networking, and security controls are governed by the hosting organization. You'll support and deploy the application within those guidelines.

Key Responsibilities

• Investigate, troubleshoot, and resolve application bugs and system issues across the frontend, API, database, and cloud services.
• Address confirmed defects identified through autonomous testing and human Test Engineer validation.
• Perform root-cause analysis for recurring and complex technical issues.
• Develop, test, document, and deploy reliable application fixes.
• Analyze application logs, metrics, APIs, databases, integrations, and AWS infrastructure when diagnosing issues.
• Collaborate with Test Engineers to reproduce defects and validate implemented fixes.
• Address production issues and provide technical support for application incidents.
• Support application maintenance, upgrades, dependency updates, and security-related remediation, including resolving dependency and container image vulnerability findings.
• Participate in code reviews and follow established secure coding and development practices.
• Maintain technical documentation for application fixes, system behavior, configurations, and integrations.
• Support controlled application releases and deployments, following documented procedures and runbooks.
• Follow applicable government configuration-management and change-control processes.
• Protect government, sensitive, proprietary, and Controlled Unclassified Information (CUI), when applicable, in accordance with organizational and contractual requirements.
• Follow applicable access-control, cybersecurity, data-handling, and acceptable-use requirements.

AI Model Tuning & Optimization

• Conduct scheduled reviews and tuning of AI/model performance.
• Analyze AI behavior using autonomous testing results, human validation findings, production observations, and user feedback.
• Identify patterns of inaccurate, inconsistent, incomplete, or undesirable AI behavior.
• Adjust approved prompts, configurations, model parameters, workflows, guardrails, retrieval settings, and integrations as appropriate.
• Establish baseline measurements before significant tuning activities.
• Validate proposed model/configuration changes in approved non-production environments before release.
• Collaborate with Test Engineers to independently validate AI behavior following tuning.
• Document significant model, prompt, configuration, and behavioral changes.
• Maintain appropriate traceability and version history for AI-related changes.
• Evaluate tuning results against defined quality and performance criteria.
• Monitor for regressions and unintended behavior following updates.
• Ensure model tuning activities comply with applicable government security, privacy, data-handling, and AI governance requirements.

Required Qualifications

• 3–5 years of professional software engineering or application development experience.
• 3+ years of production experience with TypeScript and Node.js, across both frontend and backend.
• Strong experience developing and maintaining production web applications.
• Demonstrated experience troubleshooting and resolving application defects.
• Strong debugging and root-cause analysis skills.
• Experience working with APIs, relational databases (PostgreSQL preferred), integrations, and distributed application components.
• Hands-on experience running and troubleshooting containerized applications on AWS, including services such as ECS/Fargate, ECR, RDS, S3, SQS, and IAM, and diagnosing issues through CloudWatch logs and metrics.
• Working experience with Docker and container-based deployments.
• Experience with Git and modern source-control workflows.
• Familiarity with CI/CD and controlled software deployment processes.
• Comfort working with restricted access, least-privilege permissions, and approval-gated changes, and able to diagnose issues without unrestricted access to production systems.
• Experience collaborating with QA/Test Engineers to reproduce and resolve defects.
• Understanding of secure software development principles.
• Strong technical documentation and communication skills.

Preferred Qualifications

• Experience with Next.js, tRPC, Prisma, or similar TypeScript full-stack frameworks and ORMs.
• Experience with additional AWS services such as EventBridge, DynamoDB, Secrets Manager, and KMS.
• Ability to read and modify infrastructure as code (AWS CDK in TypeScript or CloudFormation), including deploying through change sets.
• Experience developing or maintaining applications incorporating generative AI or Large Language Models.
• Experience integrating applications with Amazon Bedrock or equivalent managed LLM APIs, including structured output, streaming, retries, and usage tracking.
• Experience with prompt engineering, model configuration, retrieval (RAG/vector search), evaluation, or optimization.
• Familiarity with AI model evaluation and performance measurement.
• Experience with autonomous or agentic AI systems.
• Experience supporting U.S. federal government or Department of Defense applications.
• Experience deploying or supporting applications in government-accredited cloud environments (e.g., FedRAMP, DoD Impact Level 4/5).
• Familiarity with how government AWS regions differ from commercial AWS, such as FIPS endpoints and services or AI models that aren't available.
• Experience in shared or managed hosting environments, where a platform team owns the landing zone, networking, and IAM, and application teams deploy within assigned boundaries.
• Experience deploying through DevSecOps pipelines where security scans (static analysis, dependencies, container images) must pass before a release is promoted.
• Experience supporting applications in environments with limited or no internet access, using private container registries, pinned or vendored dependencies, and offline install and verification procedures.
• Experience accessing systems through CAC-authenticated virtual desktops, VPNs, or bastion hosts.
• Experience with application monitoring and observability.
• Familiarity with government cybersecurity, CUI, access-control, and change-management requirements.
• Python experience, particularly for AI evaluation or scripting.
• AWS Certified Developer – Associate or AWS Certified SysOps Administrator – Associate.

Security & Eligibility Requirements

This position supports systems and environments that require U.S. Government access authorization. Candidates must:

• Be a U.S. Person (U.S. citizen or lawful permanent resident). We are unable to sponsor employment visas for this position.
• Be based in the United States.
• Be able to successfully complete the background investigation and adjudication required for the position.
• Be eligible to obtain and maintain the required Public Trust determination for the assigned government program.
• Be eligible to obtain and maintain access to applicable DoD/government information systems, including completion and approval of DD Form 2875 – System Authorization Access Request (SAAR) when required.
• Complete required cybersecurity, information assurance, privacy, and security-awareness training.
• Comply with government and organizational requirements governing credentials, system access, sensitive information, source code, application data, and acceptable use.
• Maintain continued eligibility for government system access throughout employment when required by the assigned program.

What Success Looks Like

Success in this role means the application remains stable, secure, reliable, and continuously improving. Confirmed defects are addressed efficiently and through appropriate change-control processes. Root causes are identified and documented, fixes are independently validated, and recurring problems lead to broader technical improvements where appropriate.

AI tuning should produce measurable improvements in the accuracy, consistency, reliability, and usefulness of the platform's AI capabilities while maintaining appropriate security, human oversight, traceability, and change control.