Top Software Engineer Jobs in Kansas City, MO

Develop and maintain internal applications and AI agents using Microsoft Power Platform, APIs, databases, Copilot Studio, and Azure. Support Agile delivery, automated testing, enterprise integrations, conversational AI, intelligent automation, security and compliance standards, performance monitoring, documentation, and cross-functional solution design. The role is remote with occasional travel and offers foundational development experience.

Designs and directs development of scalable software systems using AI-assisted engineering practices. Owns architecture, APIs, data models, testing strategy, security, reliability, observability, deployment, and production operations. Decomposes work for AI agents, validates generated code and tests, leads incident response, and coaches engineers on effective AI-enabled development. Requires full-stack experience, modern server-side development, event-driven systems, cloud infrastructure, regulated-data security, and production use of agentic AI.

Leads enterprise software development, platform integrations, custom scripts, and cloud architecture. Manages the software development lifecycle from requirements through deployment, collaborates with stakeholders, mentors engineers, and directly contributes to frontend, backend, and cloud solutions. Oversees third-party enterprise tools, databases, APIs, serverless systems, QA coordination, technical processes, and cross-departmental engineering initiatives.

Builds simulation infrastructure and software-in-the-loop sensor simulation products that help customers test and validate autonomous driving, drone delivery, eVTOL, robotics, and other physical AI systems safely at scale.

Build and own backend-focused product features from planning through deployment. Responsibilities include updating data models, developing external API integrations, resolving production bugs, maintaining application security and performance, writing documentation, and collaborating with product, design, and engineering teams. The role primarily uses Python, Django, Celery, PostgreSQL, and Django ORM, with opportunities to work with TypeScript, JavaScript, AWS, Terraform, and Docker.

Provide technical implementation, configuration, integration, and customer support for real-time Concurrent Real-Time products. Assist with system setup, benchmarking, latency optimization, troubleshooting, training, demos, and proof-of-concept deployments. Collaborate with R&D to reproduce issues and validate fixes, produce documentation and solution guides, support pre-sales, and travel to customer sites (30–40%).

Develops, tests, maintains, and sustains software applications using APIs, low-code/no-code platforms, BPMN automation, MuleSoft, .NET, and SQL Server. Translates requirements into program specifications, supports application design and modifications, and contributes to testing, documentation, and reporting. The role requires agile and hybrid development experience, a MuleSoft certification, DoW-approved IAT Level I certification, a relevant degree, and an active Secret clearance.

Lead and mentor a software engineering team, provide technical guidance, drive architecture and engineering excellence, manage sprint execution, collaborate on product roadmaps, ensure scalable and reliable systems, foster continuous improvement, and support recruiting and onboarding. The role requires balancing technical strategy with business impact while developing high-performing engineers.

Build and maintain full-stack software using TypeScript, Go, and Python, including backend, frontend, and architectural development. Collaborate with developers, designers, product managers, and Department of Defense stakeholders to develop AI-powered solutions, take products from concept to launch, conduct code reviews, and support customers through travel when needed.

Drive technical direction and architecture across teams for enterprise retail software. Improve platform reliability and performance, scope customer-facing features, mentor engineers, de-risk large work, and embed AI-native practices (LLMs/agents) into engineering workflows.