AI-Native Software Engineer, Senior

Office presence: minimum 5 days per week; location(s): Alpharetta, GA; Atlanta, GA; Bedminster, NJ; Dallas, TX. No relocation offered.

Responsibilities

• Design, develop, and deploy AI-enabled applications and intelligent workflow automations using modern LLM technologies.
• Build and orchestrate agentic workflows leveraging frameworks such as LangGraph and similar orchestration platforms.
• Develop multi‑step and multi‑agent solutions including routing, planning, tool utilization, workflow execution, and escalation patterns.
• Implement retrieval‑augmented generation (RAG), vector search, and context management strategies to improve AI accuracy and effectiveness.
• Establish evaluation frameworks, testing methodologies, and release controls for AI‑enabled solutions.
• Design and build scalable backend services and APIs using Python frameworks such as FastAPI, Flask, or Django.
• Integrate AI solutions with enterprise systems, databases, event streams, and approved APIs.
• Develop secure service contracts, validation frameworks, retry mechanisms, and observability capabilities.
• Ensure enterprise‑grade security, governance, auditability, and access controls across all integrations.
• Develop end‑to‑end applications spanning backend services, data platforms, integrations, and user‑facing interfaces.
• Build modern web experiences and workflow‑driven applications using contemporary front‑end technologies.
• Collaborate with stakeholders to rapidly prototype, iterate, and productionize solutions that solve real business challenges.
• Contribute reusable platform components, libraries, and software assets that accelerate adoption across teams.
• Apply secure‑by‑design principles including authentication, authorization, secrets management, and compliance‑aligned logging.
• Implement automated testing, CI/CD pipelines, monitoring, tracing, alerting, and performance optimization.
• Ensure reliability through resilient system design patterns such as retries, timeouts, rate limiting, and graceful degradation.
• Leverage AI‑assisted development tools to accelerate coding, testing, documentation, debugging, and delivery.
• Work directly with business leaders and stakeholders to understand objectives, translate requirements into technical solutions, and influence decisions.
• Communicate complex technical concepts to non‑technical audiences and balance trade‑offs between speed, scale, cost, security, and maintainability.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience delivering production‑grade applications and services.
• Experience building scalable backend services and RESTful APIs using Python frameworks such as FastAPI, Flask, or Django.
• Experience deploying and operating applications in cloud or enterprise environments.
• Experience integrating enterprise systems through APIs, databases, event‑driven architectures, or service‑oriented platforms.
• Experience implementing CI/CD pipelines, containerization technologies, and automated testing frameworks.
• Experience developing software solutions that leverage LLM capabilities and AI‑assisted workflows.
• Strong software engineering fundamentals: system design, object‑oriented programming, data modeling, and architecture.
• Proficiency in Python development and API design best practices.
• Experience with relational databases, SQL, and modern data persistence technologies.
• Understanding of distributed systems, asynchronous processing, and system reliability patterns.
• Knowledge of software security, authentication, authorization, secrets management, and audit controls.
• Strong understanding of observability, monitoring, performance analysis, troubleshooting, and production support.
• Excellent verbal and written communication skills.
• Demonstrated ability to use AI coding assistants and AI‑powered engineering tools to improve development velocity and software quality.
• Experience building software solutions that responsibly incorporate LLM capabilities, structured prompting, tool calling, validation, and human‑in‑the‑loop controls.
• Knowledge of agent‑based architectures and workflow automation technologies.
• Hands‑on experience with agent orchestration frameworks such as LangGraph or similar.
• Experience implementing RAG architectures, vector databases, embeddings, and AI grounding strategies.
• Familiarity with workflow orchestration platforms such as Temporal, Airflow, Celery, or comparable solutions.
• Experience with event‑driven architectures and messaging technologies such as Kafka or cloud‑native messaging services.
• Knowledge of modern API gateways, OAuth2, OpenID Connect (OIDC), and secure enterprise integration patterns.
• Ability to turn ambiguous business challenges into scalable technical solutions and work closely with business stakeholders in highly collaborative environments.