Full Stack Engineer Visa Sponsorship Jobs in Maryland
Maryland's full stack engineer job market centers on the Baltimore-Washington corridor, where federal contractors like Northrop Grumman, Leidos, and Booz Allen Hamilton regularly hire for visa-sponsored roles alongside a growing commercial tech sector. Bethesda, Rockville, and Baltimore are the primary hiring hubs for international engineers seeking H-1B sponsorship in the state.
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Get Access To All JobsSenior Software Engineer - Full Stack & Generative AI
The Senior Software Engineer will serve as a pseudo-lead and strong individual contributor, driving the development of modern full-stack applications with integrated Generative AI capabilities to support Client's regulatory technology initiatives. This role combines deep technical expertise in Angular-based UI development, microservices architecture, cloud infrastructure, and cutting-edge AI/ML technologies, while providing technical mentorship and architectural guidance to the team.
Key Responsibilities
Full Stack Development: Design, develop, and maintain scalable full-stack applications with Angular frontends and microservices-based backends, ensuring seamless integration and optimal performance
API & Microservices Architecture: Build and optimize RESTful and GraphQL APIs, design microservices architectures, and implement efficient inter-service communication patterns
Generative AI Integration: Architect and implement Generative AI solutions including LLM integration, prompt engineering, RAG (Retrieval-Augmented Generation) pipelines, and AI-powered features into production applications
Cloud Infrastructure: Design and deploy cloud-native solutions on AWS, leveraging serverless architectures, containerization, and managed services for scalability and reliability
Database Design & Optimization: Implement efficient database schemas, optimize queries, and manage both SQL and NoSQL databases to support application requirements
Technical Leadership: Provide technical guidance and mentorship to team members, lead code reviews, establish best practices, and drive architectural decisions
AI/ML Model Integration: Collaborate with data science teams to integrate ML models, implement model serving infrastructure, and ensure responsible AI practices including bias monitoring and explainability
Performance & Quality: Ensure applications meet performance benchmarks, implement comprehensive testing strategies, and maintain high code quality standards
Qualifications:
- 7+ years of software engineering experience with full-stack development
- Frontend Expertise: 3+ years of production experience with Angular (latest versions), TypeScript, RxJS, NgRx/state management, and responsive UI design
- Backend Expertise: Strong proficiency in Java and/or Python for API and microservices development
- API Development: Proven experience designing and implementing RESTful APIs and/or GraphQL services
- Cloud & DevOps: Hands-on experience with AWS services (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, etc.) and containerization (Docker, Kubernetes)
- Database Proficiency: Experience with both relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
- Generative AI Experience: 1+ years working with LLMs (OpenAI, Anthropic, AWS Bedrock), prompt engineering, vector databases, and embedding models
Preferred Qualifications:
- Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks
- Background implementing RAG architectures with vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
- Knowledge of fine-tuning techniques, model evaluation, and AI safety practices
- Experience with real-time data processing and streaming architectures (Kafka, Kinesis)
- Familiarity with event-driven architectures and asynchronous messaging patterns
- Understanding of security and compliance requirements in regulated financial environments
- Experience with microservices patterns (circuit breakers, service mesh, distributed tracing)
- Contributions to open-source projects or technical publications in AI/ML domains
Skills & Competencies:
- Full Stack Mastery: End-to-end ownership of features from UI to database, with deep understanding of frontend-backend integration patterns
- Architectural Thinking: Ability to design scalable, maintainable architectures that balance business needs, technical constraints, and future growth
- AI/ML Integration: Practical knowledge of integrating Generative AI capabilities into production systems, including handling latency, costs, and reliability challenges
- Technical Problem-Solving: Strong debugging and troubleshooting skills across the full technology stack, including AI model behavior and performance issues
- Collaboration & Communication: Excellent ability to work with cross-functional teams, translate business requirements into technical solutions, and communicate complex concepts clearly
- Pseudo-Lead Capabilities: Self-motivated to drive initiatives, mentor peers, facilitate technical discussions, and influence technical direction without formal management responsibilities
- Quality & Testing Focus: Strong commitment to automated testing (unit, integration, e2e), code quality, and continuous improvement
- Learning Agility: Rapid adoption of new technologies and frameworks, particularly in the fast-evolving AI/ML landscape
Key Technologies:
- Frontend: Angular (16+), TypeScript, RxJS, NgRx, HTML5/CSS3, JavaScript
- Backend: Java (Spring Boot), Python (FastAPI, Flask), Node.js
- APIs: RESTful services, GraphQL (Apollo), gRPC
- Generative AI: AWS Bedrock, OpenAI API, LangChain, vector databases, embedding models, prompt engineering frameworks
- Databases: PostgreSQL, MongoDB, DocumentDB, DynamoDB, Redis, Vector databases (pgvector, OpenSearch)
- Cloud Platform: AWS (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, Bedrock, SageMaker, CloudWatch)
- Microservices & Integration: Docker, Kubernetes, service mesh, API Gateway, message queues (SQS, SNS, Kafka)
- DevOps & CI/CD: GitLab CI/CD, Jenkins, Terraform, CloudFormation, monitoring and observability tools
- Testing: Jest, Jasmine, Karma, JUnit, PyTest, Selenium, Cypress
What Makes This Role Unique
This position offers the opportunity to work at the intersection of modern full-stack development and cutting-edge Generative AI technology within a mission-critical regulatory environment. You'll have the autonomy of a strong individual contributor while exercising technical leadership influence, working on challenging problems that require both breadth and depth of expertise across the entire technology stack and emerging AI capabilities.
Senior Software Engineer - Full Stack & Generative AI
The Senior Software Engineer will serve as a pseudo-lead and strong individual contributor, driving the development of modern full-stack applications with integrated Generative AI capabilities to support Client's regulatory technology initiatives. This role combines deep technical expertise in Angular-based UI development, microservices architecture, cloud infrastructure, and cutting-edge AI/ML technologies, while providing technical mentorship and architectural guidance to the team.
Key Responsibilities
Full Stack Development: Design, develop, and maintain scalable full-stack applications with Angular frontends and microservices-based backends, ensuring seamless integration and optimal performance
API & Microservices Architecture: Build and optimize RESTful and GraphQL APIs, design microservices architectures, and implement efficient inter-service communication patterns
Generative AI Integration: Architect and implement Generative AI solutions including LLM integration, prompt engineering, RAG (Retrieval-Augmented Generation) pipelines, and AI-powered features into production applications
Cloud Infrastructure: Design and deploy cloud-native solutions on AWS, leveraging serverless architectures, containerization, and managed services for scalability and reliability
Database Design & Optimization: Implement efficient database schemas, optimize queries, and manage both SQL and NoSQL databases to support application requirements
Technical Leadership: Provide technical guidance and mentorship to team members, lead code reviews, establish best practices, and drive architectural decisions
AI/ML Model Integration: Collaborate with data science teams to integrate ML models, implement model serving infrastructure, and ensure responsible AI practices including bias monitoring and explainability
Performance & Quality: Ensure applications meet performance benchmarks, implement comprehensive testing strategies, and maintain high code quality standards
Qualifications:
- 7+ years of software engineering experience with full-stack development
- Frontend Expertise: 3+ years of production experience with Angular (latest versions), TypeScript, RxJS, NgRx/state management, and responsive UI design
- Backend Expertise: Strong proficiency in Java and/or Python for API and microservices development
- API Development: Proven experience designing and implementing RESTful APIs and/or GraphQL services
- Cloud & DevOps: Hands-on experience with AWS services (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, etc.) and containerization (Docker, Kubernetes)
- Database Proficiency: Experience with both relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
- Generative AI Experience: 1+ years working with LLMs (OpenAI, Anthropic, AWS Bedrock), prompt engineering, vector databases, and embedding models
Preferred Qualifications:
- Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks
- Background implementing RAG architectures with vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
- Knowledge of fine-tuning techniques, model evaluation, and AI safety practices
- Experience with real-time data processing and streaming architectures (Kafka, Kinesis)
- Familiarity with event-driven architectures and asynchronous messaging patterns
- Understanding of security and compliance requirements in regulated financial environments
- Experience with microservices patterns (circuit breakers, service mesh, distributed tracing)
- Contributions to open-source projects or technical publications in AI/ML domains
Skills & Competencies:
- Full Stack Mastery: End-to-end ownership of features from UI to database, with deep understanding of frontend-backend integration patterns
- Architectural Thinking: Ability to design scalable, maintainable architectures that balance business needs, technical constraints, and future growth
- AI/ML Integration: Practical knowledge of integrating Generative AI capabilities into production systems, including handling latency, costs, and reliability challenges
- Technical Problem-Solving: Strong debugging and troubleshooting skills across the full technology stack, including AI model behavior and performance issues
- Collaboration & Communication: Excellent ability to work with cross-functional teams, translate business requirements into technical solutions, and communicate complex concepts clearly
- Pseudo-Lead Capabilities: Self-motivated to drive initiatives, mentor peers, facilitate technical discussions, and influence technical direction without formal management responsibilities
- Quality & Testing Focus: Strong commitment to automated testing (unit, integration, e2e), code quality, and continuous improvement
- Learning Agility: Rapid adoption of new technologies and frameworks, particularly in the fast-evolving AI/ML landscape
Key Technologies:
- Frontend: Angular (16+), TypeScript, RxJS, NgRx, HTML5/CSS3, JavaScript
- Backend: Java (Spring Boot), Python (FastAPI, Flask), Node.js
- APIs: RESTful services, GraphQL (Apollo), gRPC
- Generative AI: AWS Bedrock, OpenAI API, LangChain, vector databases, embedding models, prompt engineering frameworks
- Databases: PostgreSQL, MongoDB, DocumentDB, DynamoDB, Redis, Vector databases (pgvector, OpenSearch)
- Cloud Platform: AWS (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, Bedrock, SageMaker, CloudWatch)
- Microservices & Integration: Docker, Kubernetes, service mesh, API Gateway, message queues (SQS, SNS, Kafka)
- DevOps & CI/CD: GitLab CI/CD, Jenkins, Terraform, CloudFormation, monitoring and observability tools
- Testing: Jest, Jasmine, Karma, JUnit, PyTest, Selenium, Cypress
What Makes This Role Unique
This position offers the opportunity to work at the intersection of modern full-stack development and cutting-edge Generative AI technology within a mission-critical regulatory environment. You'll have the autonomy of a strong individual contributor while exercising technical leadership influence, working on challenging problems that require both breadth and depth of expertise across the entire technology stack and emerging AI capabilities.
Full Stack Engineer Job Roles in Maryland
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Search Full Stack Engineer Jobs in MarylandFull Stack Engineer Jobs in Maryland: Frequently Asked Questions
Which companies sponsor visas for full stack engineers in Maryland?
Federal contractors and defense IT firms are among the most active visa sponsors for full stack engineers in Maryland. Companies like Leidos, Booz Allen Hamilton, Northrop Grumman, Perspecta, and SAIC have consistent H-1B filing histories. Beyond defense, firms in the biotech corridor around Rockville and commercial technology companies in the Baltimore metro also sponsor regularly. DOL Labor Condition Application disclosure data is a reliable way to verify which employers have sponsored recently.
Which visa types are most common for full stack engineer roles in Maryland?
The H-1B is the most common visa for full stack engineers in Maryland, as software development roles typically qualify as specialty occupations requiring a bachelor's degree in computer science or a related field. L-1B visas apply for intracompany transferees with specialized knowledge. Engineers already authorized through OPT or STEM OPT are frequently hired before transitioning to H-1B sponsorship. TN visas are available specifically for Canadian and Mexican nationals in qualifying engineering roles.
Which cities in Maryland have the most full stack engineer sponsorship jobs?
Bethesda and Rockville, in Montgomery County, account for a large share of Maryland's visa-sponsored full stack engineering roles, driven by the density of federal agencies and contractors nearby. Baltimore hosts a growing commercial tech and cybersecurity sector with active hiring. Columbia and Greenbelt also see consistent demand, particularly from government IT contractors operating near federal facilities. The Interstate 270 technology corridor connecting Gaithersburg to the D.C. border is especially active.
How to find full stack engineer visa sponsorship jobs in Maryland?
Migrate Mate is built specifically for international job seekers and lets you filter full stack engineer roles by state, including Maryland, while surfacing employers with verified visa sponsorship history. This saves significant time compared to parsing general job listings with no sponsorship clarity. Focus your search on the Baltimore-Washington corridor and filter for H-1B-sponsoring employers. Roles at federal contractors often require security clearance eligibility, so note that requirement before applying.
Are there any Maryland-specific considerations for full stack engineers seeking visa sponsorship?
Maryland's proximity to federal agencies means many full stack engineering roles involve government contracts, which can introduce security clearance requirements that complicate or limit sponsorship for some international candidates. Employers on federal contracts must also comply with prevailing wage requirements set by the Department of Labor when filing H-1B petitions. The University of Maryland's strong computer science program feeds local talent pipelines, and some graduates leverage OPT or STEM OPT extensions while pursuing long-term sponsorship arrangements with Maryland employers.
What is the prevailing wage for sponsored full stack engineer jobs in Maryland?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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