Staff AI Python Software Engineer

Growth Acceleration Partners•Colorado Springs, CO

About The Position

Founded in 2007, Growth Acceleration Partners (GAP) is a consulting and technology services company. We consult, design, build and modernize revenue-generating software and data engineering solutions for clients. With modernization services and AI tools, we help businesses achieve a competitive advantage through technology. GAP’s remote, integrated engineering teams use end-to-end solutions to innovate and align with your business goals. We have 600+ English-speaking engineers based in Latin America and approximately 20 U.S.-based engineers. With some of the highest customer satisfaction scores in the industry, GAP’s focus is customer and employee success. GAP is a woman-owned company headquartered in Austin Texas. We are a values-based company focused on growing our people by investing in education, onsite English classes and training in the latest technologies, including AI, data analytics and machine learning. Our goal is to provide solutions for our customers that help them achieve critical business outcomes, while enabling our GAPSters and our communities to attain long-term success. We are looking for a Staff AI Python Software Engineer to lead the design and implementation of AI-powered backend systems within a fast-growing, product-driven environment. This is a high-impact, product-focused role where you will take ownership from problem definition to delivery. You will operate with a high level of autonomy, translating product needs into scalable technical solutions and driving execution across the development lifecycle. This role requires a strong combination of Staff-level Python engineering expertise and deep experience working within product teams. You should be comfortable owning a full feature or epic end-to-end — from defining the implementation approach to breaking down tasks, estimating effort, and delivering the solution. Additionally, this is an AI-native engineering role. You are expected to have advanced, hands-on experience using AI assistants, coding agents, and automation workflows, not only as support tools but as multipliers of your productivity. You should be comfortable delegating work to AI systems, orchestrating workflows, and accelerating delivery through these tools.

Requirements

6+ years of experience in software engineering with strong Python expertise
Proven experience working in product-driven environments
Experience owning end-to-end delivery of features or epics
Strong experience in system design and scalable architectures
Advanced hands-on experience using AI tools, coding agents, or AI-assisted development workflows
Strong experience in several of the following areas: Backend & Architecture: Python, scalable system design, distributed systems
Product Engineering: Experience working closely with product teams, owning features end-to-end
AI-Native Development: Advanced use of AI assistants, coding agents, and automation workflows
AI & LLMs: Experience integrating LLM APIs, NLP systems, or AI-driven features
Cloud & DevOps: AWS, GCP, or Azure, Docker, CI/CD pipelines
APIs & Data: REST APIs, data processing, databases
Voice Systems (Plus): STT/TTS integrations or conversational systems
Advanced English proficiency
Strong product mindset and business understanding
High ownership and autonomy
Ability to move fast and deliver iterative solutions
Strong decision-making and prioritization skills
Mentorship and leadership capabilities

Nice To Haves

Experience with RAG architectures or AI agent frameworks
Experience building AI-first or voice-enabled products
Exposure to real-time systems or conversational interfaces

Responsibilities

Own the design and delivery of backend systems and AI-powered features from concept to production
Translate product requirements into scalable architecture and implementation strategies
Break down features or epics into tasks, estimates, and delivery plans
Manage and own the full development lifecycle, including prioritization and release flow
Build and integrate systems leveraging LLMs, NLP, and voice technologies (STT/TTS)
Use AI tools and agents to accelerate development, debugging, and decision-making
Delegate and orchestrate work across AI-assisted workflows and automation tools
Collaborate closely with product, design, and engineering teams to drive outcomes
Mentor engineers and influence technical direction and best practices

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