Full Stack Developer (Python, Java, Docker, Kubernetes)

Ignite IT

Job Overview

Location

Suitland, Maryland, United States

Employment Type

Full-time

Work Arrangement

Remote

Sector

Information Technology & Software

Experience Level

Senior (5-8 years)

Application Deadline

July 17, 2026

About the Company

Ignite IT is a dynamic IT consulting firm dedicated to partnering with federal agencies to deliver breakthrough digital innovations. The company prides itself on a culture of advancement and growth, empowering its employees to excel and contribute to impactful projects.

Ignite IT specializes in providing world-class solutions across various domains, including cybersecurity, Agile methodologies, DevSecOps, Cloud computing, AI, Low-code/No-code development, and Human-Centered Design. With offices in Virginia and Florida, Ignite IT holds prestigious certifications such as CMMI-SVC/3, ISO 20000-1:2018, ISO 27001:2013, and ISO 9001:2015, underscoring its commitment to quality and excellence in government contracting.

Job Description

Ignite IT is seeking a highly skilled Full Stack Developer to join our team, focusing on critical projects for the US Census Bureau. In this pivotal role, you will be instrumental in designing, developing, and maintaining sophisticated routing and scheduling algorithms.

These algorithms are the backbone of the Mojo field operations control system, ensuring maximum operational efficiency and data-driven accuracy for vital national survey workflows. You will be responsible for architecting modular, scalable optimization services capable of handling both massive batch schedules and real-time, on-demand routing challenges.

This is an opportunity to contribute to high-impact national initiatives, leveraging your expertise in full-stack development to build robust and intelligent systems.

To apply for this role, click the Apply button on this page and follow the instructions.

Required Skills

PythonJavaDockerKubernetesOR-ToolsRouting AlgorithmsScheduling AlgorithmsOptimization SystemsGraph TheoryClusteringHeuristic TechniquesApproximation TechniquesREST APIsData PipelinesCI/CDLoggingMetricsMonitoringPerformance TuningParallel ProcessingLarge Dataset HandlingEnterprise Control Systems

Key Responsibilities

  • Design and implement vehicle routing and scheduling algorithms using OR-Tools to generate optimal field assignments.
  • Develop clustering algorithms to group workloads geographically and minimize travel time/cost.
  • Implement constraint models (capacity, time windows, skills, priorities, survey rules) within the optimizer.
  • Integrate the optimizer with the Mojo control system APIs for job intake, execution, and results publishing.
  • Build batch and real-time optimization modes to support both scheduled and on-demand routing.
  • Refactor optimizer components into modular, extensible strategy interfaces for new routing heuristics.
  • Implement data preprocessing pipelines to normalize locations, distances, and travel matrices.
  • Develop automated test harnesses validating solution correctness against known datasets and constraints.
  • Implement “solution quality” scoring metrics (distance, balance, SLA adherence, cost) to evaluate goodness of routes.
  • Create regression benchmarks comparing new algorithm performance vs. baseline outputs.
  • Add parallel processing and scaling support to handle large route sets and high agent counts.
  • Instrument services with logging and metrics to track runtime, solver performance, and solution quality.
  • Package optimizer services for CI/CD deployment with reproducible builds and environment configs.
  • Document routing logic, constraints, integration points, and operational runbooks.
  • Provide production support, tuning, and continuous improvement of optimization heuristics and performance.

Qualifications

  • 5+ years’ experience designing and implementing routing, scheduling, or optimization systems.
  • Strong algorithmic background including graph theory, clustering, and heuristic/approximation techniques.
  • Proficiency in Python or Java for building optimization services and supporting tooling.
  • Experience developing scalable, high-performance services integrated with enterprise control systems (e.g., Mojo).
  • Demonstrated ability to design test harnesses validating both solution correctness and optimization quality.
  • Experience implementing performance tuning, parallel processing, and large dataset handling.
  • Familiarity with REST APIs, data pipelines, and system integration patterns.
  • Experience instrumenting systems with logging, metrics, and monitoring for operational visibility.
  • Ability to document algorithms, constraints, and operational procedures and collaborate across engineering and operations teams.
  • US Citizenship required.
  • Ability to obtain and maintain a government clearance.

Benefits & Perks

  • 401(k) with matching and 100% Vested
  • Health Insurance (3 plans to select from)
  • Dental insurance
  • Vision Insurance
  • Health savings account
  • Life insurance
  • Short Term Disability
  • Long Term Disability
  • AD&D
  • Paid time off
  • Professional development assistance
  • Training
  • Tuition reimbursement
  • Flexible schedule
  • Flexible spending account
  • Referral program
  • Paid Legal Plan

How to Apply

Join Our Communities

The US federal technology landscape is rapidly evolving, demanding advanced optimization solutions for critical national infrastructure. This role focuses on architecting and maintaining highly complex routing and scheduling algorithms for the US Census Bureau's Mojo field operations. You will leverage OR-Tools, graph theory, and advanced clustering techniques to build scalable, high-performance optimization services. Your contributions will directly enhance operational efficiency, ensure data-driven accuracy, and support real-time, on-demand routing for massive national survey workflows. This position offers significant impact on government operations and requires expertise in distributed systems and algorithmic design.

Posted Date

July 3, 2026