Senior Agentic AI UI Devleoper

📍 Job Overview

Job Title: Senior Agentic AI UI Developer

Company: Parsons Corporation

Location: Springfield, VA, United States (On-site)

Job Type: Full time

Category: Software Development / AI Engineering

Date Posted: September 01, 2026

Experience Level: 10+ years

Remote Status: On-site

🚀 Role Summary

• Develop and enhance advanced AI-enabled applications that significantly improve operational effectiveness, decision support, and mission execution for critical government initiatives.

• Architect and implement enterprise AI systems utilizing Kubernetes and micro-services, designed to support thousands of users in secure production environments.

• Drive the deployment, troubleshooting, and continuous improvement lifecycle of complex AI solutions, ensuring high availability and performance.

• Play a pivotal role in an operations organization, contributing to a tight-knit development team focused on modernizing and advancing customer missions through cutting-edge AI technology.

• Leverage extensive Python expertise for backend services, automation, AI model integration, and the development of essential tooling.

📝 Enhancement Note: The job title "Senior Agentic AI UI Developer" combined with the description's focus on "operations organization," "customer's mission into the future," and "operational effectiveness" strongly suggests this role is deeply embedded within a government or defense sector operational context, requiring a blend of UI development skills and a deep understanding of how AI impacts operational workflows and decision-making. The emphasis on Kubernetes, micro-services, and secure production environments points to a robust, scalable, and secure application development environment.

📈 Primary Responsibilities

• Design, develop, and maintain user interfaces and backend services for AI-driven applications, focusing on enhancing operational workflows and decision-making capabilities.

• Implement and manage AI models and agentic systems within a micro-services architecture, leveraging frameworks like Langchain to build sophisticated applications.

• Utilize Python for backend development, automation scripting, AI integration, and the creation of internal tooling to streamline development and operations.

• Ensure the robust deployment, monitoring, and continuous improvement of applications within secure production environments, adhering to strict security protocols.

• Collaborate closely with a small, specialized development team to define requirements, architect solutions, and deliver high-impact AI functionalities that directly support mission objectives.

• Develop and consume RESTful web services and APIs to facilitate seamless integration between different system components and external data sources.

• Troubleshoot and resolve complex technical issues related to AI systems, micro-services, and Kubernetes deployments in a production setting.

📝 Enhancement Note: While the title includes "UI Developer," the core responsibilities heavily lean towards backend development, AI integration, and system architecture (Python, Kubernetes, micro-services, AI systems). The UI aspect is present but seems to be integrated within a broader AI and operations focus. The mention of "thousands of users" and "secure production environments" implies a need for scalable, reliable, and secure development practices.

🎓 Skills & Qualifications

Education:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. Experience:

• 8+ years of overall software development experience.

• 5+ years of professional experience specifically in Python development.

• Extensive experience designing and consuming RESTful web services and APIs.

• Proven experience working with Kubernetes and micro-services architectures.

• Demonstrable experience in building and enhancing AI-enabled applications. Required Skills:

• Strong proficiency in Python for backend services, automation, AI integration, and tooling development.

• Expertise in designing and consuming RESTful web services and APIs.

• Deep understanding and practical experience with Kubernetes for container orchestration.

• Experience developing applications within a micro-services architecture.

• Proven ability to integrate or develop applications using Large Language Models (LLMs) and Agentic AI systems.

• Experience in developing AI-enabled operational workflows or mission-critical applications.

• Familiarity with software development best practices, including version control (e.g., Git) and CI/CD principles.

• Ability to obtain and maintain an active Secret level security clearance (TS preferred). Preferred Skills:

• Experience with Langchain or other LLM frameworks for building advanced AI applications.

• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their containerization services.

• Experience in troubleshooting and supporting applications in secure production environments.

• Knowledge of data science principles and machine learning operations (MLOps).

• Experience in the defense or intelligence sectors, understanding mission-specific requirements.

📝 Enhancement Note: The "10+ years" experience level derived from the AI analysis suggests a very senior individual contributor role. The strong emphasis on Python, Kubernetes, and AI/LLM frameworks indicates a need for deep technical expertise in modern software engineering and AI implementation. The security clearance requirement is paramount and should be a primary filter for candidates.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase projects demonstrating the successful design and implementation of AI-enabled applications or operational workflows.

• Provide examples of Python backend services, automation scripts, or tooling developed for efficiency or AI integration.

• Include case studies or project details that highlight experience with Kubernetes and micro-services architectures.

• Demonstrate ability to work with APIs and integrate various system components.

• Evidence of experience with LLMs, Agentic AI, or frameworks like Langchain is highly desirable. Process Documentation:

• Highlight experience in documenting development processes, including code structure, API design, and deployment procedures.

• Showcase how you've contributed to the continuous improvement of applications, including troubleshooting and performance optimization.

• Provide examples of how you have integrated AI into existing operational processes or designed new AI-driven workflows.

📝 Enhancement Note: Given the senior nature of the role and its focus on AI and operational impact, a portfolio demonstrating tangible results and complex problem-solving is crucial. Candidates should be prepared to discuss the architecture, challenges, and outcomes of their AI and software development projects, with a clear emphasis on how their work improved operational effectiveness or mission execution.

💵 Compensation & Benefits

Salary Range: $125,100.00 - $225,200.00 USD per year.

Benefits:

• Comprehensive medical, dental, and vision insurance plans.

• Generous paid time off (PTO) for work-life balance.

• Employee Stock Ownership Plan (ESOP), providing a stake in the company's success.

• 401(k) retirement savings plan with potential company match.

• Life insurance coverage for added financial security.

• Flexible work schedules to accommodate personal needs.

• Paid holidays to observe national and company-recognized holidays. Working Hours:

• Standard full-time position, typically 40 hours per week, with potential for flexible scheduling.

📝 Enhancement Note: The salary range provided is competitive for a Senior Software Developer/AI Engineer role with extensive experience and a required security clearance in the Washington D.C. metropolitan area. The benefits package is robust, reflecting Parsons Corporation's commitment to employee well-being and long-term retention. The mention of "flexible work schedules" is noteworthy for an on-site role, suggesting some degree of autonomy within the operational framework.

🎯 Team & Company Context

🏢 Company Culture

Industry: Defense, Aerospace, Intelligence, and Government Services. Parsons Corporation is a major player in providing advanced technology solutions and services to U.S. government customers, both domestically and internationally. Their work spans critical areas such as defense, security, intelligence, infrastructure, and environmental solutions.

Company Size: Parsons Corporation is a large, publicly traded company with thousands of employees globally. This provides a stable environment with ample resources, but also means processes can be more formalized.

Founded: Parsons was founded in 1944, bringing a long history of engineering and technology innovation to its government and commercial clients. This longevity suggests a deep understanding of complex project lifecycles and client needs within the federal sector.

Team Structure:

• This role is part of the Federal Solutions segment, specifically within an operations organization.

• The development team is described as "small" and "tight-knit," implying a collaborative and focused environment where individual contributions are highly visible.

• The Senior Agentic AI UI Developer will likely work closely with other developers, AI/ML engineers, operations specialists, and potentially mission stakeholders.

• Reporting structure is likely to a development lead or engineering manager within the Federal Solutions segment. Methodology:

• Emphasis on building and enhancing AI-enabled applications to drive operational effectiveness and mission execution.

• Utilization of modern software development practices, including Kubernetes and micro-services, for scalable and robust enterprise AI systems.

• Focus on deployment, troubleshooting, and continuous improvement in secure production environments.

• An agile and adaptive approach is implied by the need to "drive the customer's mission into the future."

Company Website: https://www.parsons.com/

📝 Enhancement Note: The company's long history in defense and government contracting, combined with its size, means candidates should expect a structured environment with a strong emphasis on security, compliance, and mission impact. The "small, tight-knit development team" within this large organization suggests a unique opportunity for direct influence and close collaboration.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior individual contributor role within the AI/Software Development domain, specifically focused on enhancing operations through AI. The role demands deep technical expertise in Python, AI frameworks, and cloud-native technologies, alongside an understanding of operational needs and mission execution. It sits at the forefront of integrating cutting-edge AI technologies into critical government operations.

Reporting Structure: The Senior Agentic AI UI Developer will likely report to a technical lead or engineering manager responsible for the AI development initiatives within the Federal Solutions segment. This structure allows for direct technical guidance and project oversight.

Operations Impact: The role has a direct and significant impact on operational effectiveness, decision support, and mission execution for U.S. government customers. By building and enhancing AI-enabled applications, this developer will contribute to more efficient operations, better insights, and ultimately, the success of critical national missions. The scale of deployment ("thousands of users") underscores the broad impact of this position.

Growth Opportunities:

• Technical Specialization: Deepen expertise in Agentic AI, LLMs, Langchain, Kubernetes, and micro-services, becoming a subject matter expert in these cutting-edge fields.

• Leadership Potential: Progress into technical leadership roles, such as Tech Lead or Architect, guiding smaller teams or complex projects within the AI and Federal Solutions domains.

• Cross-Functional Exposure: Gain exposure to various government missions and operational challenges, broadening understanding of defense and intelligence requirements.

• Advanced Certifications: Pursue relevant certifications in cloud technologies, AI/ML, or security clearances to enhance professional credentials and career mobility.

• Mentorship: Opportunity to mentor junior developers and share knowledge within the team, fostering a learning environment.

📝 Enhancement Note: The "Senior" title and the required experience level indicate a role focused on technical leadership and deep problem-solving rather than direct management. Growth opportunities will likely stem from increasing technical scope, project complexity, and influence within the organization's AI strategy.

🌐 Work Environment

Office Type: The role is explicitly stated as "On-site" in Springfield, VA. This suggests a traditional office environment within a Parsons Corporation facility, likely designed to support secure operations and collaborative development.

Office Location(s):

• Primary location: Springfield, VA (7500 Geoint Dr). This area is known for its proximity to government agencies and defense contractors.

• Potential for work in St. Louis, MO, as indicated by locations_alt_raw. Candidates may need to be open to relocation or occasional travel. Workspace Context:

• Collaborative Environment: As part of a "small, tight knit development team," expect a highly collaborative workspace where team members work closely together on projects.

• Technology Access: The environment will likely provide access to necessary development tools, secure network infrastructure, and potentially specialized hardware for AI model development and testing.

• Security Focus: Given the Secret clearance requirement and the nature of the work, the workspace will adhere to strict security protocols, potentially including controlled access and secure computing environments.

• Innovation Hub: The role's focus on "Agentic AI" and "driving the customer's mission into the future" suggests an environment that encourages innovation and the exploration of new technologies.

Work Schedule:

• Standard 40-hour work week is typical, with the possibility of "flexible work schedules" mentioned in benefits. This flexibility might relate to start/end times rather than full remote work, given the on-site requirement.

• The demanding nature of government missions may occasionally require extended hours or on-call support, though this is not explicitly stated.

📝 Enhancement Note: The on-site requirement in Springfield, VA, is a key factor. Candidates should be prepared for a structured, secure, and collaborative office environment. The mention of St. Louis as an alternate location suggests potential flexibility or a broader organizational presence that might influence future opportunities or initial placement.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or recruiter call to assess basic qualifications, clearance status, and alignment with company culture.

• Technical Interview(s): In-depth interviews focusing on Python proficiency, AI/LLM concepts, Kubernetes, micro-services, API design, and problem-solving skills. Expect coding challenges or live coding exercises.

• Behavioral Interview: Assessment of teamwork, communication, problem-solving approach, and how you handle challenges, particularly within an operational context.

• Manager/Team Lead Interview: Discussion about your experience, project contributions, career aspirations, and fit with the specific team dynamics.

• Security Clearance Verification: Formal process to confirm the validity and status of your Secret clearance.

Portfolio Review Tips:

• Curate Select Projects: Choose 2-3 projects that best showcase your AI development, Python backend work, and experience with complex systems (Kubernetes, micro-services).

• Focus on Impact: For each project, clearly articulate the problem, your role, the technologies used, the challenges faced, and the quantifiable results (e.g., improved efficiency, reduced errors, enhanced decision-making).

• Demonstrate AI Integration: Specifically highlight how you integrated LLMs, Agentic AI, or other AI components, and the framework (like Langchain) used.

• Technical Depth: Be prepared to discuss architectural decisions, code quality, API design principles, and deployment strategies in detail.

• Operational Relevance: Frame your project discussions to emphasize how your work contributed to operational effectiveness or mission goals, aligning with the role's core purpose.

Challenge Preparation:

• Coding Challenges: Practice Python coding problems, focusing on data structures, algorithms, and API interaction.

• System Design: Prepare to discuss how you would design an AI-enabled application using micro-services and Kubernetes, considering scalability, security, and operational needs.

• AI/LLM Scenarios: Be ready to discuss how you would approach building an agentic AI system for a specific operational task, including prompt engineering, tool integration, and response validation.

• Security Awareness: Understand the implications of working with classified information and the importance of adhering to security protocols.

📝 Enhancement Note: The emphasis on "Agentic AI UI Developer" and "operations organization" means interviewers will be looking for candidates who can bridge the gap between advanced AI technology and practical operational application. The portfolio should strongly reflect this intersection.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Language: Python (primary language for backend, AI integration, automation, tooling).

• Containerization & Orchestration: Kubernetes (for deploying and managing micro-services).

• Micro-services Frameworks: Experience with common Python micro-services frameworks (e.g., Flask, FastAPI) is likely.

• AI/LLM Frameworks: Langchain (explicitly mentioned), potentially others like Hugging Face Transformers, TensorFlow, PyTorch.

• API Development: Experience with RESTful APIs (designing and consuming).

• Version Control: Git (standard for code management).

Analytics & Reporting:

• While not explicitly mentioned, expect tools for monitoring application performance, system health, and potentially AI model performance. This could include tools like Prometheus, Grafana, ELK stack (Elasticsearch, Logstash, Kibana), or platform-specific monitoring services. CRM & Automation:

• Not directly applicable to this development role, but understanding how AI applications interact with operational systems or databases is key. This might involve interacting with enterprise databases or workflow management tools.

• CI/CD Tools: Experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions) would be beneficial for automated deployment and testing.

📝 Enhancement Note: The technology stack is heavily focused on modern, cloud-native development practices with a strong emphasis on Python and AI. Proficiency in Kubernetes and micro-services is non-negotiable. Candidates should be prepared to discuss their experience with these specific technologies and how they apply them to build robust, scalable AI solutions.

👥 Team Culture & Values

Operations Values:

• Mission Focus: A strong dedication to supporting and advancing critical government missions, ensuring that technology serves a clear purpose.

• Excellence & Agility: Embracing a culture of high performance, continuous learning, and the ability to adapt quickly to evolving mission requirements and technological advancements.

• Innovation: Fostering an environment where new ideas and cutting-edge technologies, like Agentic AI, are explored and implemented to solve complex challenges.

• Collaboration: Working effectively in a "tight-knit development team" and cross-functionally with operations and other stakeholders to achieve common goals.

• Integrity & Security: Upholding the highest standards of integrity, ethical conduct, and security protocols, especially given the sensitive nature of government work.

Collaboration Style:

• Team-Oriented: Expect close collaboration within the development team, with regular communication and knowledge sharing.

• Cross-Functional Engagement: Interaction with operations personnel to understand their needs, gather feedback, and ensure AI solutions effectively support their workflows.

• Stakeholder Communication: Ability to clearly communicate technical concepts and project progress to both technical and non-technical stakeholders.

• Problem-Solving Focused: A collective approach to identifying and resolving technical challenges, leveraging the diverse expertise within the team.

📝 Enhancement Note: The culture at Parsons, particularly within its Federal Solutions segment, is likely to be highly professional, mission-driven, and security-conscious. The emphasis on agility and innovation suggests an openness to adopting new AI technologies, balanced with the rigorous demands of government contracting.

⚡ Challenges & Growth Opportunities

Challenges:

• Integrating Cutting-Edge AI: Working with rapidly evolving Agentic AI and LLM technologies, requiring continuous learning and adaptation to new frameworks and best practices.

• Secure Production Environments: Navigating the complexities of deploying and maintaining AI applications within highly secure, often air-gapped or restricted, government systems.

• Scalability and Performance: Ensuring enterprise-level AI systems perform reliably and efficiently for thousands of users, demanding robust architecture and optimization.

• Bridging the Gap: Translating complex AI capabilities into intuitive and effective user interfaces and workflows that genuinely enhance operational effectiveness for diverse users.

• Clearance Requirements: Maintaining an active Secret clearance and adhering to all security protocols is a continuous requirement.

Learning & Development Opportunities:

• AI & ML Specialization: Opportunities to become a leader in Agentic AI, LLM integration, and MLOps within a practical, mission-critical context.

• Cloud-Native Expertise: Deepen skills in Kubernetes, micro-services, and potentially cloud platforms, essential for modern enterprise application development.

• Government Sector Insight: Gain invaluable experience and understanding of the unique challenges and opportunities within the defense and intelligence sectors.

• Advanced Training: Access to company-sponsored training, workshops, and potentially conferences related to AI, software development, and cybersecurity.

• Mentorship Programs: Benefit from or provide mentorship, fostering professional growth and knowledge transfer within the team.

📝 Enhancement Note: The challenges presented are significant but also represent prime opportunities for growth. Candidates who thrive in complex, rapidly evolving technical environments and are motivated by mission impact will find this role particularly rewarding.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex AI-enabled application you've developed. What was the operational problem it solved, what was your role, and what were the key technical challenges and outcomes?" (Focus on Agentic AI, LLMs, Python, Kubernetes)

• "How would you approach designing an AI system to assist intelligence analysts in sifting through large volumes of unstructured data? Discuss your architectural choices, key technologies, and how you'd ensure usability and accuracy." (Tests system design, AI strategy, and operational relevance)

• "Walk us through a challenging debugging scenario you encountered with a Python micro-service deployed on Kubernetes. How did you diagnose the issue, and what steps did you take to resolve it and prevent recurrence?" (Assesses troubleshooting skills and technical depth) Company & Culture Questions:

• "Parsons emphasizes 'valuing people, embracing agility, and fostering growth.' How do you see these values aligning with your approach to software development and your career aspirations, particularly within a government operations context?" (Assesses cultural fit and understanding of company values)

• "This role is part of a 'small, tight-knit development team' within a large organization. How do you approach collaboration and knowledge sharing in such an environment?" (Evaluates teamwork and communication skills)

• "Given the importance of security in our work, how do you prioritize security considerations throughout the software development lifecycle?" (Tests security awareness and responsibility) Portfolio Presentation Strategy:

• Storytelling with Data: For each project, craft a narrative that clearly outlines the problem, your solution, the technologies used, and the quantifiable impact on operational effectiveness or mission success.

• Technical Deep Dive: Be prepared to answer detailed questions about your code, architecture, API design, and deployment strategy. Use diagrams where helpful.

• Focus on AI/LLM Contribution: Explicitly detail your role in integrating AI/LLMs, the specific frameworks used (e.g., Langchain), and how they contributed to the project's success.

• Address Challenges: Be transparent about challenges faced and how you overcame them, demonstrating resilience and problem-solving skills.

• Conciseness: Aim for clear, concise explanations, respecting the interviewer's time while providing sufficient detail.

📝 Enhancement Note: Interview preparation should strongly emphasize the intersection of advanced AI development (Agentic AI, LLMs) with practical operational improvements and mission execution within a secure government environment. Candidates need to demonstrate both technical prowess and a strategic understanding of how their work contributes to larger objectives.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided Workday link.

• Tailor your resume: Highlight your 8+ years of software development experience, with a strong emphasis on 5+ years of professional Python expertise. Explicitly list your experience with Kubernetes, micro-services, RESTful APIs, and any work with LLMs or Agentic AI frameworks like Langchain. Quantify achievements wherever possible.

• Prepare your portfolio: Select 2-3 key projects that showcase your Python backend development, AI integration (especially LLMs/Agentic AI), and experience with complex architectures like micro-services on Kubernetes. Be ready to articulate the operational impact and technical details of these projects.

• Research Parsons Corporation: Understand their mission within the Federal Solutions segment, their commitment to innovation, and their values. This will help you tailor your responses during interviews.

• Practice your technical explanations: Be prepared to discuss your experience with Python, Kubernetes, AI frameworks, and API design in detail. Practice explaining complex technical concepts clearly and concisely, as you may be asked to present your portfolio or solve technical challenges.

• Confirm clearance status: Ensure your active Secret security clearance is up-to-date and readily verifiable, as this is a mandatory requirement.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.