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Programming Engineer Jobs

33 jobs found

Today

Senior Software Engineer

Civicom Carlsbad, CA

Carlsbad, CA

Today

$65k - $150k/yr Full time Senior AWS Database

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Job Description

Civicom is building high-stakes, AI-driven healthcare SaaS platforms, and this role is designed for engineers who want total ownership from problem identification through production delivery. You will work in an intense, flat environment focused on full-cycle execution, deep engineering fundamentals, and leadership through measurable outcomes.

Location: Carlsbad, CA (onsite). Must live near (or be willing to immediately relocate to) one of Civicom’s core hubs: NY/CT Border, Hanover, NH, or Carlsbad, CA.

Compensation: USD 65,000 - 150,000 per year (full-time).

What you’ll do

Identify the problem, prioritize it, design the architecture, write the code, and ship the fix with total ownership.
Translate an abstract product vision into production-ready, resilient software by breaking down complex requirements and executing independently.
Direct ownership of an elite product team building AI healthcare applications, supported by a broader network of 50+ engineers across 20 global brands within Civicom.

Core technologies

You’ll work across modern stacks including TypeScript with React, Node.js, MySQL, PostgreSQL, DynamoDB, and Python for AI integration work. Experience with Java EE or the ability to navigate new enterprise environments on demand is also important.

What you bring

Advanced proficiency in TypeScript (React framework) and Node.js.
High competence with MySQL, PostgreSQL, and DynamoDB.
Working knowledge of Python and the willingness to operate across enterprise domains such as Java EE.
Strong engineering fundamentals, a rapid learning curve, and mastery across key modern layers.
Ability to take an abstract product vision, break down complex requirements, and ship production-ready resilient software autonomously.
Clear communicator who can explain dense AI and engineering concepts in simple, razor-sharp English to non-technical stakeholders or healthcare executives.
High energy with zero ego: drive real strategic change, stand up for ideas, and pivot to execute the best idea in the room regardless of whose it was.
Forever learner: enter conversations to learn, listen more than you talk, ask questions, and treat every experience as an opportunity to learn.
Long-term legacy mindset: stay committed to the mission long enough to see compounding results from what you architect today.
Grit and intensity: operate with a whatever-it-takes approach during critical releases or complex bug fixes.
A true full-cycle fixer: address issues directly rather than only flagging them for others.

Benefits and compensation highlights

401(k)
Dental insurance
Health insurance
Paid time off
Vision insurance
Competitive base salary plus quarterly performance bonuses tied directly to high-impact execution
Modified profit-sharing bonus each quarter
Transfer of 10% of company stock appreciation to employees

Application question

Give an example of something you achieved that shows the ability to get results.

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Today

Mid-Level Software Engineer

Leidos Tucson, AZ

Tucson, AZ

Today

$87k - $157k/yr Full time Backend Developer APIs Cloud Operations

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Job Description

Leidos is seeking a Mid-Level Full Stack Software Engineer for the Chinook Program supporting an Intelligence Community customer. The position focuses on designing, developing, testing, and deploying secure web and microservices capabilities that address GEOINT mission needs in an Agile DevSecOps environment.

Role Responsibilities

Design, develop, test, and deploy software solutions that support the customer’s GEOINT mission.
Participate in agile development sprints, including daily stand-ups, sprint planning, and retrospectives.
Build and maintain secure, containerized applications using technologies such as Docker, Kubernetes, and AWS.
Develop RESTful APIs and user-facing interfaces using modern tooling such as React, Node.js, and Flask or Spring Boot.
Collaborate with mission users and product managers to refine requirements and improve user experience.
Support DevSecOps pipelines and help ensure code aligns with security and accreditation standards.
Participate in code reviews and mentor junior developers as needed.
Complete team-assigned tasks prioritized by the product owner.

Required Qualifications

US citizenship required per contract.
Bachelor’s degree in Computer Science, Software Engineering, or related field with 4 to 8 years of prior relevant experience, or Master’s with 2 to 6 years of prior relevant experience.
Active Top Secret/SCI with the ability to successfully pass a Polygraph examination.
Proficiency with web technologies including HTML, CSS, JSON, Ajax, and REST APIs.
Proficiency with object-oriented programming in Python, Java, or JavaScript.
Proficiency with advanced programming in Go.
Proficiency with front-end and back-end frameworks including one or more of: React, Angular, Vue.js, jQuery, Spring Boot, Django, Node.js, Flask, or Svelte.
Proficiency with cloud development using AWS, Azure, or similar cloud platforms.
Proficiency with relational databases: MySQL, PostgreSQL, or SQL Server.
Proficiency with operating systems including Windows and Linux.
Proficiency with Git as a version control system.
Deep understanding of modern software design patterns and coding standards.
Experience architecting, developing, and delivering complex software systems into production.
Experience with CI/CD tools such as GitLab CI and Jenkins, and agile collaboration tools such as JIRA and Confluence.
Familiarity with cloud environments such as AWS (including C2S or GovCloud) and containerization technologies including Docker and Kubernetes.
Understanding of secure coding practices and government system accreditation processes (for example, RMF and STIGs).
Strong, self-motivated desire to learn new languages, tools, frameworks, and techniques.

Technologies

Docker, Kubernetes, AWS, REST APIs, React, Node.js, Flask, Spring Boot, HTML, CSS, JSON, Ajax, Python, Java, JavaScript, Go, Angular, Vue.js, jQuery, Django, Svelte, Azure, MySQL, PostgreSQL, SQL Server, Windows, Linux, Git, GitLab CI, Jenkins, JIRA, Confluence, RMF, STIGs

Preferred Qualifications

Frontend web development with UI/UX experience.
NoSQL database experience with OpenSearch or Elasticsearch.
Cloud exposure supporting multi-cloud architectures across AWS, IBM, Google, Azure, and Oracle.
Experience with specific AWS services including S3, SQS, SNS, EC2, CloudFormation, and RDS.
Experience working on a customer contract or in the Intelligence Community (IC).
Familiarity with geospatial tools and standards: GeoServer, PostGIS, OGC APIs, and ESRI ArcGIS.
Exposure to Infrastructure-as-Code using Terraform and Ansible.
Relevant certifications such as AWS Certified Developer, Security+, SAFe Practitioner, or similar.

Clearance Requirements

Active Top Secret/SCI with the ability to successfully pass a Polygraph examination.

Benefits

Competitive compensation
Health and Wellness programs
Income Protection
Paid Leave and Retirement

Location and Work Schedule

Tucson, AZ (onsite).

This position may be performed in the following locations. Note: Gaithersburg, MD is the program’s primary work location.

Gaithersburg, MD
Alexandria, VA
Chantilly, VA
Englewood, CO
St. Louis, MO
Tucson, AZ

Compensation and Posting Details

Salary Range: USD 87,100 - 157,450 per yearly
Pay Range: $87,100.00 - $157,450.00
Minimum Experience: 4 years
Original Posting: July 10, 2026

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Today

Lead Machine Learning Engineer

Capital One New York, NY

New York, NY

Today

$215k - $246k/yr Full time Ai Ml Artificial Intelligence Big Data

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Job Description

Capital One is hiring a Lead Machine Learning Engineer to join an Agile team focused on designing, developing, and bringing machine learning applications into production at scale. The role includes ML architecture, production monitoring and governance, and building cloud-based, distributed ML systems with strong testing and CI/CD practices, including Responsible and Explainable AI.

Key Responsibilities

Design, build, and/or deliver machine learning models and components to address real-world business needs in collaboration with Product and Data Science teams.
Guide ML infrastructure decisions by applying knowledge of ML modeling practices and tradeoffs, including model and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Address complex problems through application code development and testing, ML model development and validation, and automated tests and deployment.
Work within a cross-functional Agile team to build and improve software that supports big data and machine learning applications.
Retrain, maintain, and monitor models after deployment to ensure continued performance in production.
Use or build cloud-based architectures and platforms to deliver optimized ML models at scale, including AWS and Kubernetes.
Build optimized data pipelines to supply data for ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful releases of ML models and application code.
Manage code to reduce vulnerabilities, apply risk-aware governance for models, and follow Responsible and Explainable AI best practices.
Use programming languages such as Python, Go, Scala, or Java.

Required Qualifications

Bachelor’s Degree.
At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience building, scaling, and optimizing ML systems.

Preferred Qualifications

Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field.
3+ years of on-the-job experience building production-ready data pipelines that feed ML models.
3+ years of experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
2+ years of experience developing performant, resilient, and maintainable code using Python or Go.
2+ years of experience with data gathering and preparation for ML models.
2+ years of people leader experience.
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
Experience designing, implementing, and scaling infrastructure using Kubernetes.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating performance.
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Experience leveraging interactive AI tooling to accelerate productivity, using capabilities beyond basic code completion.

Technologies

Python, Go, Scala, Java
AWS, Kubernetes
scikit-learn, PyTorch, Dask, Spark, TensorFlow
Azure, Google Cloud Platform

Location

New York, NY (onsite)

Salary Information

$215,200 - $245,600 per year for New York, NY.

Performance-based incentive compensation may be available, which could include cash bonus(es) and/or long term incentives (LTI).

Additional listed ranges: Cambridge, MA; McLean, VA; San Francisco, CA; San Jose, CA.

Additional Information

Expected to accept applications for a minimum of 5 business days.
No agencies please.
Capital One is an equal opportunity employer (EOE), committed to non-discrimination under applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider qualified applicants with a criminal history in line with applicable laws.
If you need accommodation for applying, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com.
For technical support or recruiting process questions, email Careers@capitalone.com.
Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site.
Capital One Financial includes multiple entities; posted locations may correspond to different Capital One entities.

Immigration Authorization Statement

At this time, Capital One will not sponsor a new applicant for employment authorization or offer any immigration-related support for this position (including H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1, O-1, or other forms of work authorization requiring employer immigration support).

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Today

Distinguished Machine Learning Engineer

Capital One McLean, VA

McLean, VA

Today

$269k - $307k/yr Full time Manager Ai Ml Artificial Intelligence

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Job Description

Capital One is seeking a Distinguished Machine Learning Engineer in McLean, VA (onsite) to provide technical leadership across the productionization of machine learning applications and systems at scale. The role focuses on building and evolving intelligent solutions while ensuring strong availability and performance in business-critical environments.

Responsibilities

Deliver machine learning models and software components that address complex business challenges in the financial services industry, partnering with Product, Architecture, Engineering, and Data Science teams
Drive the creation and ongoing evolution of machine learning models and software enabling state-of-the-art intelligent systems
Lead large-scale machine learning initiatives with customer needs as a central priority
Use cloud-based architectures and technologies to deliver optimized machine learning models at scale
Optimize data pipelines to ensure reliable, high-quality inputs for machine learning models
Promote and evangelize best practices across engineering and modeling lifecycles
Support recruiting efforts and contribute to nurturing and retaining top engineering talent

Requirements

Bachelor’s degree
At least 10 years of experience designing and building data-intensive solutions using distributed computing
At least 6 years of experience programming in C, C++, Python, or Scala
At least 3 years of experience with the full machine learning development lifecycle using modern technology in a business critical setting
Master’s degree
3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed machine learning models
2+ years of experience using Dask, RAPIDS, or in High Performance Computing
2+ years of experience with the PyData ecosystem, including NumPy, Pandas, and Scikit-learn
Ability to communicate complex technical concepts clearly to a range of audiences
Demonstrated machine learning industry impact through conference presentations, papers, blog posts, or open source contributions
Ability to attract and develop high-performing software engineers with an inspiring leadership style
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position

Technology

C, C++, Python, Scala
Dask, RAPIDS
NumPy, Pandas, Scikit-learn

Compensation

USD 269,100 - 307,200 per year

Benefits

Eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)

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Today

Lead Machine Learning Engineer

Capital One McLean, VA

McLean, VA

Today

$197k - $225k/yr Full time Manager Agentic Ai Systems AI

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Job Description

Lead the engineering and deployment of AI enablement capabilities for Finance teams, including end-user use cases and production AI/ML systems.

Responsibilities

Work with cross-functional partners including engineers, data scientists, product managers, and designers to deliver AI-powered products for associates and customers.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation and experimentation.
Build and operate large language model inference features, similarity search, guardrails, governance, observability, and agentic AI capabilities.
Fine-tune, develop, and evaluate machine learning models and foundation models.
Contribute within a cross-functional Agile team to create and enhance software leveraging state-of-the-art AI and ML capabilities.
Provide technical vision and thought leadership to shape the long-term roadmap for pioneering AI systems.
Apply a broad mix of Open Source and SaaS AI technologies.
Use knowledge of ML modeling techniques and common issues to inform ML infrastructure decisions.
Retrain, maintain, and monitor models in production.
Build optimized data pipelines to supply training and inference datasets for ML models.
Maintain code quality to reduce vulnerabilities, ensure responsible governance from a risk perspective, and follow best practices for Responsible and Explainable AI.

Requirements

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications

Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
7+ years of experience designing, developing, delivering, and supporting AI services at scale
3+ years building production-ready data pipelines that feed ML models
3+ years on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
3+ years developing AI and ML algorithms or technologies using Python
2+ years of experience with Retrieval Augmented Generation (RAG)
2+ years of experience with data gathering and preparation for ML models
2+ years of people leader experience
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
Experience leveraging interactive AI tooling to accelerate productivity, using capabilities beyond basic code completion
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, or Azure

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
Retrieval Augmented Generation (RAG)
AWS Bedrock
Google Cloud
Azure

Location & Work Mode

McLean, VA 22101 (onsite)

Compensation

USD 197,300 - 225,100 per year
Salary ranges by location:
- Cambridge, MA: $197,300 - $225,100
- McLean, VA: $197,300 - $225,100
- New York, NY: $215,200 - $245,600
Candidates hired in other locations are subject to the pay range for that location, and the actual annualized salary offered is reflected in the candidate’s offer letter.

Benefits

Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
Comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being.

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Today

Machine Learning Engineer - Training & Simulation Systems (Engineer Machine Learning 2)

HII Virginia Beach, VA

Virginia Beach, VA

Today

$95k - $122k/yr Full time Artificial Intelligence Data Analytics Data Pipeline

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Job Description

HII Mission Technologies is seeking a full-time, on-site Machine Learning Engineer to design, develop, and deploy training and simulation capabilities for the Advanced Training Domain (ATD) System that supports U.S. Navy operational readiness. The role applies machine learning and data-driven methods to increase training realism, adaptability, and performance.

Role Responsibilities

Participate in Agile sprint planning and execution across cross-functional engineering teams
Design, develop, and deploy machine learning models to support simulation accuracy, data analytics, performance prediction, and system-behavior modeling
Build data pipelines for collection, preprocessing, labeling, and training using structured and unstructured Navy training data
Integrate ML models into Linux-based training systems using containers, APIs, or embedded inference engines
Troubleshoot, optimize, and maintain ML workflows, including performance tuning, error analysis, and model explainability
Produce supporting materials such as architecture diagrams, data-flow documentation, model cards, evaluation reports, and code commentary
Perform developer testing in lab environments and aboard ship when required
Provide occasional on-site support for installations, model validation, and user evaluations, with travel of up to 10%
Complete additional related duties as assigned to support project and organizational needs

Required Qualifications

2 years of relevant experience with a Bachelor’s degree in a related field, OR
0 years of experience with a Master’s degree in a related field, OR
High school diploma or equivalent and 6 years of relevant experience
Experience developing and deploying ML models using Python frameworks such as PyTorch, TensorFlow, or Scikit-learn
Hands-on experience with Linux-based development environments
Familiarity with Agile/Scrum methodologies
Experience implementing data pipelines, feature engineering, and model training and evaluation workflows
Ability to troubleshoot complex issues related to software, data, or models
Ability to obtain DoD Information Assurance Technician (IAT) Level II certification or higher (examples: Security+ CE, CCNA Security, CySA+) within 3 months of hire if not currently held
Must be a U.S. Citizen
Must hold a current or active DoD Secret clearance

Preferred Qualifications

Degree in Computer Science, Data Science, ML/AI, Engineering, or related technical field
IAT Level II certification or higher (e.g., Security+ CE, CCNA Security, CySA+)
Experience with high-fidelity training systems, simulation environments, or Navy combat systems
Experience deploying ML models in operational or real-time systems (for example, REST APIs, message queues, embedded inference)
Familiarity with ActiveMQ, messaging systems, or streaming-data frameworks
Experience with MLOps tools such as GitLab CI/CD, Docker, Podman, Kubernetes, or virtualization technologies
Background in data analysis for mission systems, sensor data, or tactical environments
Experience with Jira, Git, or Subversion

Technologies and Tools

Python, PyTorch, TensorFlow, Scikit-learn
Linux
Agile, Scrum
Security+ CE, CCNA Security, CySA+
Containers, APIs, embedded inference engines

Impact, Growth & Development

Support U.S. Navy readiness by engineering ML solutions that improve training fidelity and system performance
Work with software engineers, data engineers, analysts, and end users to address operationally relevant challenges
Build skills through hands-on experience with high-fidelity simulation systems, real-world training data, and modern ML/AI toolchains
Contribute to innovations shaping future combat system training platforms

Compensation and Employment Details

Location: Virginia Beach, VA (onsite)
Employment type: Full Time, Salaried, Exempt
Level: Mid
Salary range: $95,004 - $122,000 per year
Travel: 0 - 10%

Benefits

Best-in-class medical, dental, and vision plan choices
Wellness resources
Employee assistance programs
Savings Plan Options (401(k))
Financial planning tools
Life insurance
Employee discounts
Paid holidays and paid time off
Tuition reimbursement
Early childhood and post-secondary education scholarships

Physical Qualifications

May require work in an office, industrial, shipboard, or laboratory environment
Must be capable of climbing ladders and tolerating confined spaces and a range of temperature conditions during shipboard or testing activities

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Today

Agentic AI Engineer

RTX Corporate Arlington, VA

Arlington, VA

Today

$96k - $182k/yr Full time Agentic Ai Systems Ai Engineering Artificial Intelligence

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Job Description

RTX BBN Technologies is hiring an Agentic AI Engineer to design, develop, and deploy agentic AI systems. This hybrid role in Arlington, VA focuses on Python-based frameworks, evaluation-driven experimentation, and translating research outcomes into deployable prototypes, with TS/SCI security clearance requirements.

Key Responsibilities

Design, build, and deploy agentic AI systems that support autonomous reasoning, planning, and multi-step task execution.
Create and optimize Python-based frameworks and tools to enable scalable agent architectures.
Incorporate advanced agentic AI research into practical applications through rapid prototyping of new capabilities.
Work with research scientists and engineers to plan experiments, evaluate system performance, and deliver high-quality technical documentation.
Lead or contribute to peer-reviewed publications, white papers, and internal research briefs.
Partner with product and engineering teams to convert research insights into real-world impact.

Required Qualifications

Experience with Python, including building production-quality systems.
Experience developing agentic or autonomous AI systems.
Experience applying latest research in agentic AI, including LLM architectures, planning algorithms, or autonomous reasoning.
Experience designing and running experimental evaluations for AI models or agents.
Technical writing skills, including authoring research papers, preprints, or detailed technical reports.
Ability to collaborate across cross-functional research and engineering teams.
Ability to obtain and maintain a U.S. government issued security clearance is required, and U.S. citizenship is required.

Technologies

Python

Preferred Qualifications

Graduate degree in computer science, machine learning, artificial intelligence, or a related field.
Experience with reinforcement learning, multi-agent systems, or cognitive architectures.
Contributions to open-source AI frameworks or agentic toolkits.
Familiarity with cloud-native development, distributed compute, or containerized workflows.
A track record of published research in top AI/ML conferences or journals.

What You Will Learn

Advanced techniques in agentic AI, including tool-use, planning algorithms, multi-agent coordination, and memory architectures.
Methods for translating emerging research into production-ready systems at scale.
Best practices for evaluating autonomous AI behaviors with an emphasis on safety, reliability, and alignment.
Collaboration workflows across research, engineering, and product teams.
Exposure to a broad range of generative AI, reinforcement learning, and orchestration frameworks.

Benefits

100% paid tuition program
Generous 401k company match
Retirement Contribution
Performance-based incentive plans
Onsite gym and game room
Paid parental leave
Paid time off
Employee discounts
Medical, dental, vision, and life insurance
Short-term disability
Long-term disability
Flexible spending accounts
Flexible work schedules
Employee assistance program
Employee Scholar Program
Parental leave
Holidays

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