Principal Engineer, AI Factory

Banyan Software•Washington, DC

15h

About The Position

We are seeking a highly experienced and hands-on Principal Engineer to drive the engineering and execution efforts for our new AI Application Modernization Factory. This is a deeply technical and hands-on role critical for designing, building, and delivering the high-quality, AI-enabled software development automation tools and services that are the core products of the factory. The ideal candidate will possess expert-level cloud mastery, a deep-seated commitment to engineering excellence, and a proven ability to translate complex product requirements into highly scalable, secure, and resilient technical implementations, operating within the established architectural standards.

Requirements

Bachelor’s degree in Computer Science or equivalent technical area and/or experience.
8+ years of progressive experience in Software Engineering, with significant time spent in a Principal Engineer, Staff Engineer, or Architect role.
Expert-level experience with Amazon Web Services (AWS) (e.g., EC2, Lambda, EKS, S3, RDS) and proven mastery of Infrastructure-as-Code (IaC) using Terraform for provisioning and managing large-scale cloud environments.
Deep expertise in container (e.g., Docker / Kubernetes) and serverless (e.g., Lambda, Azure Functions) technologies for building highly scalable and resilient distributed architectures.
Deep history of hands-on software engineering, making significant code contributions, and leading technical design and implementation. A player/coach who can provide thorough code reviews and upskill team members (both human and agentic).
Strong experience in building B2B and enterprise-scale applications and systems, successfully translating business capability and objectives into technical solutions.
Hands-on skills working with SQL and No-SQL databases.
Strong application development skills, including experience in modern technology languages such as Typescript, Python, C#, Java, Go, or Ruby.
Familiarity with advanced UI frameworks like React, NextJS and Vite.
Strong command of automation and modern DevSecOps practices, including deep experience with CI/CD platforms like GitHub Actions, GitLab CI, or similar tools.
Proven experience in advanced engineering practices, including code refactoring, modern design patterns (adaptor, onion, n-tier), Domain-Driven Design (DDD), and application security.
Uses pragmatic, quality-driven development habits and Twelve-Factor App fundamentals, including clean code, automation, stateless services, and clear configuration management.
Demonstrated experience working in Agile methodologies (e.g., Scrum, Kanban) and a comfort level with ambiguity and rapid changes common in early-stage product development.
Exceptional team collaboration and communication skills (both verbal and written), with a proven ability to work under competing priorities and manage expectations effectively with technical and business stakeholders.

Nice To Haves

Experience building and operating a multi-tenant SaaS (Software as a Service) solution at scale.
Prior experience leading a modernization or re-platforming effort for a large enterprise or B2B application.
Experience in multi-agent frameworks (e.g., crewAI, autogen) for sophisticated AI workflow orchestration.
Experience integrating GenAI capabilities using frameworks like Langchain or LlamaIndex.
Experience developing AI Agents along developing and connecting to MCP Servers and tools.
Familiarity with Context Engineering, agentic architectures, Hybrid Vector Databases (including knowledge graphs) and advanced proficiency in Prompt Engineering and Guardrail Design for enterprise AI safety.

Responsibilities

Act as a hands-on Principal Engineer, making significant code contributions, performing complex code reviews, and serving as the highest technical escalation point for engineering challenges in the AI Application Modernization Factory.
Design, build, and deploy the core AI-enabled software development automation tools and services (e.g., custom agents, GenAI integrations) with a keen focus on legacy software analysis, requirement extraction, and architectural discovery leveraging multi-modal GenAI capabilities.
Own the technical design and implementation of features and services, ensuring they adhere to the factory’s established technical architecture, design patterns, and engineering best practices.
Implement Generative AI capabilities, including RAG (and GraphRAG) systems and LLM orchestration, into the automation tools to build new intelligent features and automate business processes.
Drive the technical strategy for developing automation tools that aid in modernizing legacy applications to a cloud-native, microservices, or serverless architecture across major cloud providers (AWS, Azure, GCP).
Serve as a top technical authority, defining and enforcing engineering standards and quality across product areas. Lead, mentor, and coach senior and junior engineers, fostering a culture of technical excellence, continuous improvement, and knowledge sharing.
Drive an ownership mindset by taking pride in work quality and seeing projects through to successful deployment and operation. Set a high bar for engineering standards, security, and operational excellence.
Apply strong analytical and structured problem-solving skills including technical problem definition, functional decomposition, and hypothesis-driven investigation to resolve complex engineering and operational challenges, with the ability to make confident technical decisions when problems or solutions are not well-defined (ambiguity).
Implement secure-by-design principals along with robust cloud-native observability tooling to debug and monitor complex distributed systems, ensuring secure, high performance and high availability operations.