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Guidehouse

Advises agencies and runs regulated operations

Lead Software Developer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeMcLean, VA, USAIn-person

About the Job

Requirements

  • Must be able to obtain and maintain a Federal or Department of Defense Public Trust, with approved adjudication before onboarding.
  • A bachelor's degree is required.
  • At least eight years of progressive software development experience, including hands-on leadership of complex efforts involving legacy application enhancement or modernization, backend service development, data integration, cloud delivery, and production support.
  • Demonstrated experience leading technical design and delivery for a software development team, including work planning, estimation, task decomposition, code reviews, engineering standards, mentoring, and resolution of cross-team technical dependencies.
  • Ability to make and clearly communicate technical decisions, balance delivery speed with security and maintainability, and translate business and architecture objectives into executable engineering plans.
  • Strong hands-on proficiency in one or more modern programming languages and associated frameworks, such as Python, Java, JavaScript/TypeScript, C#/.NET, Go, or comparable technologies, along with SQL, RESTful API development, automated testing, and maintainable software design.
  • Experience engineering AI-enabled applications using foundation-model APIs or machine-learning services, including prompt design and retrieval-augmented generation.

Responsibilities

  • Provide hands-on technical leadership for a development team, establishing implementation direction, engineering standards, delivery priorities, and accountability for technical outcomes.
  • Lead solution design, technical discovery, estimation, work decomposition, and implementation planning for complex modernization features and releases.
  • Conduct architecture, design, and code reviews; enforce secure coding, testing, documentation, and maintainability standards; and ensure timely remediation of technical debt and quality issues.
  • Mentor developers through pairing, technical coaching, constructive review feedback, reusable patterns, and knowledge sharing to improve team capability and consistency.
  • Identify and communicate technical risks, dependencies, tradeoffs, and escalation needs; coordinate resolution across architecture, security, data, DevSecOps, vendor, and product teams.
  • Analyze legacy applications, data structures, interfaces, dependencies, and business rules to identify safe modernization increments.
  • Enhance and refactor legacy applications and databases while developing new APIs, services, automation, and cloud-native components using suitable modern languages and frameworks, including Python, Java, JavaScript/TypeScript, C#/.NET, Go, or comparable technologies.
  • Implement phased modernization patterns that allow modern and legacy capabilities to operate concurrently without disrupting mission operations.
  • Build and maintain an integrated data layer providing consistent, governed shared-data access through APIs, events, reusable data services, canonical models, and transformation components.
  • Develop interoperability between legacy applications, modern services, vendor platforms, and analytics capabilities using synchronous APIs, asynchronous messaging, events, batch processing, and change-data patterns.
  • Implement data mapping, validation, transformation, lineage, reconciliation, synchronization, error handling, and auditability across systems of record.
  • Design, prototype, and productionize AI capabilities such as retrieval-augmented generation, semantic search, document intelligence, classification, summarization, intelligent assistants, and agent-supported workflows when appropriate to business needs.
  • Integrate foundation models and machine-learning services with enterprise applications, APIs, and governed data using prompt orchestration, embeddings, vector search, tools, and model-agnostic service patterns.
  • Design versioned API, event, and data contracts that decouple consumers from legacy implementation details and support controlled schema evolution.
  • Preserve validated business rules and compliance controls while progressively separating tightly coupled application and data components.
  • Develop resilient services using retries, timeouts, idempotency, dead-letter queues, transaction controls, and failure-recovery mechanisms.
  • Implement secure authentication, authorization, encryption, secrets management, and least-privilege access across application and data interfaces.
  • Create unit, integration, contract, regression, and performance tests to verify business behavior and end-to-end interoperability.
  • Develop AI evaluation suites and operational controls for accuracy, groundedness, relevance, latency, cost, security, privacy, prompt injection, sensitive-data exposure, model drift, and other use-case-specific risks.
  • Implement responsible AI controls, including guardrails, traceability, audit logging, model and prompt versioning, human-in-the-loop review, fallback behavior, and ongoing monitoring aligned with organizational and Federal requirements.
  • Use CI/CD pipelines, infrastructure as code, code reviews, automated security scanning, and feature controls to deliver changes safely and repeatedly.
  • Instrument application and data flows with centralized logging, metrics, tracing, health checks, alerts, and operational dashboards.
  • Troubleshoot defects across application code, data flows, APIs, events, databases, AWS services, identity controls, network paths, and deployment environments.
  • Document code design, data models, mappings, interface contracts, migration decisions, test evidence, deployment procedures, and operational runbooks.
  • Collaborate in Agile delivery with architects, developers, data engineers, DevSecOps, security, vendors, product teams, and Federal stakeholders.

Desired Qualifications

  • Candidates with an active Public Trust or suitability are preferred.

About the Company

Guidehouse

Advises agencies and runs regulated operations

Guidehouse advises government agencies and companies in regulated industries on strategy, technology and day-to-day operations. Its work combines business advice with software implementation and ongoing management, so a client uses the same firm to plan a change, build the systems and run the resulting processes. Teams modernize cloud platforms, apply data analysis and artificial intelligence, and redesign organizations to meet operating and regulatory requirements. Clients pay for consulting projects and technology work or outsource continuing business functions to its managed services teams. Guidehouse was founded in 2018 and is headquartered in McLean, Virginia.

Company size
10,001+
Company stage
Acquired
Total funding
$750K
Headquarters
McLean, VA
Founded
2018

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