Architect - AI Engineering
Summary
Lead the design, hardening, and scaling of agentic AI systems from prototype to production using LangGraph, Python, FastAPI, and cloud platforms like AWS or Azure.
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We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.
Experience:8+ Years
Requirements
About the Role
We are looking for an experienced Architect to lead the design, hardening, and scaling of agentic AI systems — taking prototype-stage LLM applications and evolving them into production-grade, enterprise-ready platforms. This role sits at the intersection of AI engineering and software architecture, requiring hands-on depth in agentic frameworks alongside strong fundamentals in backend systems design and cloud deployment.
Key Responsibilities
Agentic AI Development
- Design and build agentic workflows using frameworks such as LangGraph, and tools like Claude Code, to orchestrate multi-step, tool-using AI agents
- Own prompt engineering strategy — designing, testing, and iterating on prompts for reliability, consistency, and cost efficiency
- Evaluate and integrate LLM capabilities into broader application architectures
Prototype-to-Production Engineering
- Take early-stage AI prototypes and refactor them into robust, maintainable, production-grade systems
- Identify and remediate technical debt, brittle logic, and scalability bottlenecks common in fast-built AI proofs-of-concept
- Establish engineering rigor (testing, observability, error handling, versioning) around previously ad hoc AI systems
Backend Engineering
- Architect and develop backend services in Python, using FastAPI and async programming patterns
- Optimize application performance, latency, and throughput for AI-driven workloads
- Design clean, well-documented APIs that support both internal and external consumption
Software Architecture & Design
- Apply sound software architecture principles and design patterns to ensure systems are modular, scalable, and maintainable
- Make and document key architectural decisions (system design, data flow, integration patterns, trade-offs)
- Set technical standards and provide architectural guidance to engineering teams
Cloud & Infrastructure
- Design and deploy solutions on AWS and/or Azure, leveraging cloud-native services for compute, storage, and orchestration
- Ensure systems are built with security, cost-efficiency, and scalability in mind from a cloud architecture standpoint
Required Skills & Experience
Area | Expectation |
Agentic AI Frameworks | Hands-on experience with LangGraph, Claude Code, or comparable agent orchestration tools |
Prompt Engineering | Demonstrated experience designing and refining LLM prompts for production use cases |
Python Engineering | Strong proficiency in Python, FastAPI, async/await patterns, and performance optimization |
Software Architecture | Solid grounding in design patterns, system design, and architecture for production systems |
Cloud Platforms | Working experience with AWS and/or Azure (compute, storage, deployment pipelines) |
Systems Thinking | Proven ability to take a prototype and scale it into a reliable, production-ready system |
Ideal Candidate Profile
- 8+ years of overall software engineering experience, with a meaningful portion in AI/LLM-based systems
- Comfortable operating as an individual architect/senior IC — able to both write code and make architectural calls
- Experience working in fast-moving, ambiguous environments where systems evolve from PoC to production under time pressure
- Strong communication skills to justify architectural decisions to both technical and non-technical stakeholders