Senior Software Engineer Architect

Applied Information Sciences•Reston, VA

1d•Hybrid

About The Position

At AIS, we are looking for more than just skills - we're looking for driven individuals who are passionate about making a difference, eager to grow, and aligned with our core principles. Working@AIS At AIS, we are dedicated to providing our employees with diverse opportunities to grow their careers while supporting a variety of impactful projects. For this position, we are seeking a talented individual to join AIS as a Senior Software Architect. Core Knowledge & Skills: Operates as a multi-domain subject matter expert (e.g., Security, Data) with industry depth, defines enterprise patterns, and guides adoption across solutions. Work & Complexity: Plans and directs the most complex, cross-functional, mission-critical initiatives, and evaluates industry standards to drive innovation and intellectual property. Quality & Independence: Acts independently with organization-wide influence, sets visionary bars for quality, reliability, and delivery practices. Teamwork & Communication: Models company values, mentors across the organization, builds formal networks with decision makers, and serves as an external spokesperson. Consulting & Engagement: Advises executives on strategy, steers long-range planning and new lines of business, and delivers thought-leading presentations at the highest technical level. As your initial project assignment, you will support the unique needs of our client as a Senior Software Engineer Architect.

Requirements

15+ years of experience in solution architecture, application development, and enterprise system design
Proven expertise in .NET/C#, ASP.NET, and modern application architecture patterns
Experience designing and delivering cloud-based, distributed systems (PaaS-focused environments preferred)
Hands-on experience with AI/ML solutions, including LLM workflows, prompt engineering, and production AI systems
Strong experience with databases (relational, NoSQL, graph) and data architecture
Expertise in API design and integration patterns (REST, HTTP, gRPC, etc.)
Demonstrated ability to translate business needs into technical solutions and lead full lifecycle delivery
Strong stakeholder engagement skills with experience working across executive leadership, business teams, and engineering organisations
Ability to operate effectively in fast-paced, ambiguous, and deadline-driven environments

Nice To Haves

Experience building document intelligence pipelines, including classification, extraction, and metadata analysis
Knowledge of vector databases, retrieval architectures, and AI-assisted workflow automation
Experience with Python-based automation and AI engineering
Familiarity with frontend frameworks (React, Angular, JavaScript, HTML/CSS)
Exposure to IoT systems, C++, and low-level engineering concepts
Experience defining operating models, process re-engineering, and business transformation initiatives
Background in mentoring engineers and establishing architectural governance frameworks
Strong understanding of system performance, fault tolerance, and distributed system failure patterns

Responsibilities

Lead the design and delivery of end-to-end AI and enterprise solutions, from business discovery through architecture, implementation, and production support
Partner with business units, customers, and senior leadership to translate ambiguous requirements into scalable, outcome-driven systems
Architect and implement LLM-based solutions, including document intelligence, retrieval systems, vector search, and AI-driven workflows
Design modern cloud-native and distributed systems, including APIs, integrations, data models, and automation pipelines
Re-engineer business processes to eliminate manual work, improve decision-making, and optimise operational efficiency
Provide hands-on technical leadership, including coding, design reviews, mentoring, and engineering guidance
Establish architecture standards, reusable patterns, and delivery frameworks to improve team scalability and consistency
Advise stakeholders on technology strategy, trade-offs, risks, and implementation approaches across complex initiatives