Description

Key Responsibilities

Hands-On Engineering & Prototyping

• Write production code. Dedicate a significant portion of your time to writing high-quality code, building custom internal AI developer tools, and constructing reusable AI components.
• Build proofs of concept. Rapidly prototype end-to-end AI-native workflows, integration patterns, and custom Large Language Model (LLM) gateways that demonstrate immediate value to clients.
• Implement tooling. Integrate AI-assisted coding tools (e.g., GitHub Copilot, Cursor), prompt engineering frameworks, and retrieval-augmented generation (RAG) workflows into diverse client environments.

Solution Architecture & Systems Design

• Design big-picture architecture. Architect scalable, secure, enterprise-grade AI-native SDLC frameworks tailored to each client's ecosystem.
• Multi-cloud integration. Design robust architectures spanning AWS, Azure, and modern frontend/serverless platforms such as Vercel.
• Agentic workflows. Design and deploy agentic systems in which autonomous AI agents handle complex development lifecycle tasks — multi-agent code reviews, automated unit testing, and legacy system refactoring.
• Enterprise guardrails. Embed compliance, IP protection, security, and bias-mitigation protocols within every AI pipeline you design.

Client Consulting & Strategic Leadership

• Cross-domain adaptability. Rapidly analyze distinct business domains and translate each client's industry constraints into a specific AI SDLC strategy.
• Technical advisory. Serve as a trusted advisor to client stakeholders (CTOs, VPs of Engineering), communicating complex AI concepts effectively to technical and non-technical audiences.
• AI maturity assessment. Evaluate client engineering organizations, identify SDLC bottlenecks, and define roadmaps for AI engineering automation and Developer Experience (DevEx) optimization.

Qualifications & Requirements

Education

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.

Experience

• 8+ years of professional software engineering and software architecture experience.
• 2+ years in technology consulting, professional services, or a client-facing environment.
• Proven track record of architecting and shipping complex, production-grade enterprise software systems.

Technical Skills

• Polyglot developer: Advanced proficiency across modern languages and frameworks, including Python, Java, Node.js, React, Next.js, and Angular.
• Cloud ecosystems: Hands-on architecture experience on AWS (e.g., Bedrock) and Azure (e.g., Azure OpenAI Service), with deployment experience on Vercel.
• GenAI expertise: Deep understanding of foundational LLM frameworks, vector databases, RAG architecture, and fine-tuning / prompt engineering patterns.
• DevOps & infrastructure: Strong mastery of CI/CD pipelines, automated testing, containerization (Docker, Kubernetes), and infrastructure as code.

Consulting Mindset

• Excellent communication, presentation, and storytelling skills, with the ability to manage client expectations and confidently handle pushback

Key Skills

Education

Bachelor's or Master's degrees