{"schemaVersion":"jobsearcher.job.v1","id":"4dc55b8c7c6d80e9f9a24519","url":"https://jobsearcher.com/jobs/4dc55b8c7c6d80e9f9a24519","canonicalUrl":"https://jobsearcher.com/jobs/4dc55b8c7c6d80e9f9a24519","title":"Senior Software Development Engineer (Remote)","description":"Overview:\n\nGovCIO is currently hiring for a Senior Fullstack Engineer to design, build, and deliver modern federal applications with intuitive user interfaces, AWS cloud backends, and AI-powered features. This is a hands-on senior engineering position: the majority of time is spent designing and writing production software on AWS and AI-driven systems, with additional responsibility for mentoring engineers at earlier career stages and contributing to technical direction. Prior experience delivering software for the Department of Veterans Affairs (VA) is required. This position will be located in the Continental United States (CONUS) and will be remote.\n\nResponsibilities:\nDesigns, architects, and codes applications using a React/Redux frontend and a Python backend built on AWS Lambda Powertools and Boto3, working with AWS services such as API Gateway, Athena, Aurora PostgreSQL, Bedrock, CloudFormation, CloudFront, CloudWatch, Cognito, DynamoDB, ECS, EventBridge, Glue, IAM, KMS, Lambda, OpenSearch, RDS, S3, SageMaker, SNS, SQS, Step Functions, Textract, and VPC.\nBuilds and delivers Intelligent Document Processing (IDP) systems handling large volumes of digital and scanned documents, including classification, extraction, and validation workflows built on generative AI foundation models.\nOwns significant portions of the solution end to end, and partners with architects and other senior engineers on integrations with adjacent systems.\nMakes and documents design decisions, and is accountable for the purpose, constraints, and tradeoffs behind them.\nDesigns and refines prompt and context engineering strategies, and defines how extraction results are evaluated against ground truth.\nDefines and maintains extraction schemas and data dictionaries, and keeps them aligned with downstream systems.\nMaintains and modernizes existing applications, including operational programs and procedures.\nAnalyzes and specifies systems factors, including input and output requirements, information flow, hardware and software requirements, and alternative methods of problem resolution, and recommends the approach.\nIdentifies, prioritizes, and drives down technical debt, including dependency upgrades and adoption of new platform capabilities.\nImplements and upholds a rigorous testing approach across unit, integration, and performance testing, and uses cloud-native monitoring and logging to diagnose production behavior.\nImplements quality assurance practices for AI-based extraction, including ground truth management, regression testing, and drift detection.\nEvaluates and recommends model approaches across managed foundation models, vision language models, and self-hosted or fine-tuned open-weight models on Amazon SageMaker.\nParticipates substantively in code reviews as a regular reviewer.\nAuthors and maintains design documentation, program documentation, operations documentation, runbooks, and user guides.\nDesigns and enforces controls protecting private personal and health information (PII/PHI) across document intake, extraction, and storage.\nContributes to a cross-team center of excellence for AI-assisted engineering, including runbooks, reusable skills and prompt assets, shared tooling, and engineering processes adopted by other teams.\nUses agentic AI coding tools such as Claude Code with a specification-driven approach, and helps establish review and verification expectations for generated code.\nMentors junior and mid-level engineers through pairing, code review, and coaching, and guides their certification and learning paths.\nPartners with database and cloud engineers on integration and migration efforts.\nWorks within and helps lead a multi-disciplined team including architects, human-centered designers, frontend specialists, DevOps engineers, and other software engineers.\nWorks with Product Owners and Scrum Teams on requirements decomposition, backlog refinement, estimation, and breakdown of user stories and tasks.\nTroubleshoots complex issues that span systems and teams, and communicates status and risk to stakeholders.\nQualifications:\nRequired Skills and Experience\n Bachelor’s Degree with 8 - 12 years of relevant experience, or commensurate experience.\nVA experience required. Prior hands-on experience delivering software for the Department of Veterans Affairs (VA).\nClearance Required: Ability to obtain and maintain a Public Trust / VA Tier 2 background investigation.\nDemonstrated Ability to work with Public Trust: handle sensitive and confidential information appropriately, including private personal and health information (PII/PHI).\nDemonstrated delivery ownership. Track record of taking features or systems from requirements through production and supporting them in operation.\nProficiency with Git, GitHub, and JIRA, including branching strategy, review workflow, and release practices.\nStrong system design, application programming, and \"clean code\" skills. Produces reviewable code changes, reviews the work of others substantively, creates architecture documentation and diagrams independently, and works as a peer to architects.\nDeep hands-on AWS engineering experience. Day-to-day development across AWS services, including serverless and event-driven architectures (Lambda, Step Functions, EventBridge, SQS, SNS), data and search services (S3, DynamoDB, Aurora PostgreSQL, Athena, Glue, OpenSearch), and AI/ML services (Bedrock, SageMaker, Textract), with infrastructure defined in CloudFormation.\nFundamental understanding of statistics and foundational machine learning and AI concepts, including distributions, sampling, statistical significance, supervised and unsupervised learning, overfitting, standard evaluation measures, and class imbalance.\nDeep understanding of large language models (LLMs) and vision language models (VLMs), including transformer fundamentals, differences between model families, tradeoffs among prompting, retrieval, and fine-tuning, and the choice between managed foundation models and self-hosted or fine-tuned open-weight models.\nIDP domain knowledge, including when to apply OCR, OMR, LLMs, and VLMs; data dictionaries and extraction schema design; and quality assurance practices covering ground truth, regression testing, drift detection, and measure selection.\nEffective and responsible use of agentic AI coding tools, including specification-driven prompting, verification and testing of generated output, and judgment about appropriate use.\nAbility to codify what works into runbooks, reusable assets, and repeatable processes used by other engineers and teams.\nClear written and verbal communication, including the ability to explain technical concepts and decisions to audiences with a wide range of technical backgrounds, up to and including customer stakeholders.\nProficiency in Scrum and Agile, including estimation, planning, and definition and refinement of backlog items in JIRA.\nMentorship and team leadership, including pairing, code review, coaching, and delegation that builds capability.\nInitiative and resourcefulness, including the ability to identify needed work and drive it, and to engage peer engineers, product managers, architects, and stakeholders without direction.\nAWS certification. Existing AWS certification is preferred. Candidates without current certification are expected to earn a Foundational-level certification within the first three months and a first Associate-level certification within the first eight months, and to maintain two or more Associate-level certifications thereafter.\n\nPreferred Skills and Experience\n\nBachelor’s or Master’s Degree in Computer Science, or in Science, Technology, Engineering, or Mathematics (STEM) fields.\nCurrent AWS certification at the Associate level or above, particularly Professional or Specialty.\nExperience fine-tuning, hosting, or benchmarking open-weight models, including work on Amazon SageMaker.\nCoursework or professional experience in statistics, machine learning, or data science.\nExperience with document processing, OCR, or intelligent document processing (IDP) at scale.\nExperience building shared tooling, reusable components, or engineering enablement assets used by other teams.\nExperience with reporting and analytics stacks such as Redshift, Athena, or Power BI.\nPosted Salary Range: USD $150,080.00 - USD $160,000.00 /Yr.","company":"GovCIO","rawCompany":"govcio","isRemote":true,"isActive":false,"createdAt":"2026-09-13T22:24:18.248Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1254.00","title":"Web Developers","slug":"web-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Software Development Engineer (Remote)","description":"Overview:\n\nGovCIO is currently hiring for a Senior Fullstack Engineer to design, build, and deliver modern federal applications with intuitive user interfaces, AWS cloud backends, and AI-powered features. This is a hands-on senior engineering position: the majority of time is spent designing and writing production software on AWS and AI-driven systems, with additional responsibility for mentoring engineers at earlier career stages and contributing to technical direction. Prior experience delivering software for the Department of Veterans Affairs (VA) is required. This position will be located in the Continental United States (CONUS) and will be remote.\n\nResponsibilities:\nDesigns, architects, and codes applications using a React/Redux frontend and a Python backend built on AWS Lambda Powertools and Boto3, working with AWS services such as API Gateway, Athena, Aurora PostgreSQL, Bedrock, CloudFormation, CloudFront, CloudWatch, Cognito, DynamoDB, ECS, EventBridge, Glue, IAM, KMS, Lambda, OpenSearch, RDS, S3, SageMaker, SNS, SQS, Step Functions, Textract, and VPC.\nBuilds and delivers Intelligent Document Processing (IDP) systems handling large volumes of digital and scanned documents, including classification, extraction, and validation workflows built on generative AI foundation models.\nOwns significant portions of the solution end to end, and partners with architects and other senior engineers on integrations with adjacent systems.\nMakes and documents design decisions, and is accountable for the purpose, constraints, and tradeoffs behind them.\nDesigns and refines prompt and context engineering strategies, and defines how extraction results are evaluated against ground truth.\nDefines and maintains extraction schemas and data dictionaries, and keeps them aligned with downstream systems.\nMaintains and modernizes existing applications, including operational programs and procedures.\nAnalyzes and specifies systems factors, including input and output requirements, information flow, hardware and software requirements, and alternative methods of problem resolution, and recommends the approach.\nIdentifies, prioritizes, and drives down technical debt, including dependency upgrades and adoption of new platform capabilities.\nImplements and upholds a rigorous testing approach across unit, integration, and performance testing, and uses cloud-native monitoring and logging to diagnose production behavior.\nImplements quality assurance practices for AI-based extraction, including ground truth management, regression testing, and drift detection.\nEvaluates and recommends model approaches across managed foundation models, vision language models, and self-hosted or fine-tuned open-weight models on Amazon SageMaker.\nParticipates substantively in code reviews as a regular reviewer.\nAuthors and maintains design documentation, program documentation, operations documentation, runbooks, and user guides.\nDesigns and enforces controls protecting private personal and health information (PII/PHI) across document intake, extraction, and storage.\nContributes to a cross-team center of excellence for AI-assisted engineering, including runbooks, reusable skills and prompt assets, shared tooling, and engineering processes adopted by other teams.\nUses agentic AI coding tools such as Claude Code with a specification-driven approach, and helps establish review and verification expectations for generated code.\nMentors junior and mid-level engineers through pairing, code review, and coaching, and guides their certification and learning paths.\nPartners with database and cloud engineers on integration and migration efforts.\nWorks within and helps lead a multi-disciplined team including architects, human-centered designers, frontend specialists, DevOps engineers, and other software engineers.\nWorks with Product Owners and Scrum Teams on requirements decomposition, backlog refinement, estimation, and breakdown of user stories and tasks.\nTroubleshoots complex issues that span systems and teams, and communicates status and risk to stakeholders.\nQualifications:\nRequired Skills and Experience\n Bachelor’s Degree with 8 - 12 years of relevant experience, or commensurate experience.\nVA experience required. Prior hands-on experience delivering software for the Department of Veterans Affairs (VA).\nClearance Required: Ability to obtain and maintain a Public Trust / VA Tier 2 background investigation.\nDemonstrated Ability to work with Public Trust: handle sensitive and confidential information appropriately, including private personal and health information (PII/PHI).\nDemonstrated delivery ownership. Track record of taking features or systems from requirements through production and supporting them in operation.\nProficiency with Git, GitHub, and JIRA, including branching strategy, review workflow, and release practices.\nStrong system design, application programming, and \"clean code\" skills. Produces reviewable code changes, reviews the work of others substantively, creates architecture documentation and diagrams independently, and works as a peer to architects.\nDeep hands-on AWS engineering experience. Day-to-day development across AWS services, including serverless and event-driven architectures (Lambda, Step Functions, EventBridge, SQS, SNS), data and search services (S3, DynamoDB, Aurora PostgreSQL, Athena, Glue, OpenSearch), and AI/ML services (Bedrock, SageMaker, Textract), with infrastructure defined in CloudFormation.\nFundamental understanding of statistics and foundational machine learning and AI concepts, including distributions, sampling, statistical significance, supervised and unsupervised learning, overfitting, standard evaluation measures, and class imbalance.\nDeep understanding of large language models (LLMs) and vision language models (VLMs), including transformer fundamentals, differences between model families, tradeoffs among prompting, retrieval, and fine-tuning, and the choice between managed foundation models and self-hosted or fine-tuned open-weight models.\nIDP domain knowledge, including when to apply OCR, OMR, LLMs, and VLMs; data dictionaries and extraction schema design; and quality assurance practices covering ground truth, regression testing, drift detection, and measure selection.\nEffective and responsible use of agentic AI coding tools, including specification-driven prompting, verification and testing of generated output, and judgment about appropriate use.\nAbility to codify what works into runbooks, reusable assets, and repeatable processes used by other engineers and teams.\nClear written and verbal communication, including the ability to explain technical concepts and decisions to audiences with a wide range of technical backgrounds, up to and including customer stakeholders.\nProficiency in Scrum and Agile, including estimation, planning, and definition and refinement of backlog items in JIRA.\nMentorship and team leadership, including pairing, code review, coaching, and delegation that builds capability.\nInitiative and resourcefulness, including the ability to identify needed work and drive it, and to engage peer engineers, product managers, architects, and stakeholders without direction.\nAWS certification. Existing AWS certification is preferred. Candidates without current certification are expected to earn a Foundational-level certification within the first three months and a first Associate-level certification within the first eight months, and to maintain two or more Associate-level certifications thereafter.\n\nPreferred Skills and Experience\n\nBachelor’s or Master’s Degree in Computer Science, or in Science, Technology, Engineering, or Mathematics (STEM) fields.\nCurrent AWS certification at the Associate level or above, particularly Professional or Specialty.\nExperience fine-tuning, hosting, or benchmarking open-weight models, including work on Amazon SageMaker.\nCoursework or professional experience in statistics, machine learning, or data science.\nExperience with document processing, OCR, or intelligent document processing (IDP) at scale.\nExperience building shared tooling, reusable components, or engineering enablement assets used by other teams.\nExperience with reporting and analytics stacks such as Redshift, Athena, or Power BI.\nPosted Salary Range: USD $150,080.00 - USD $160,000.00 /Yr.","datePosted":"2026-09-13T22:24:18.248Z","dateModified":"2026-09-13T22:24:18.248Z","hiringOrganization":{"@type":"Organization","name":"GovCIO","sameAs":"https://jobsearcher.com"},"jobLocationType":"TELECOMMUTE","applicantLocationRequirements":{"@type":"Country","name":"US"},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"4dc55b8c7c6d80e9f9a24519"},"url":"https://jobsearcher.com/jobs/4dc55b8c7c6d80e9f9a24519"}}