Solutions Architect

Solutions Architect

Role Overview 

As Solutions Architect you operate at the intersection of deep technical leadership and high-stakes client engagement. You will: 

• Own solution architecture and technical delivery for marquee customers, ensuring JazzX’s AGI platform unlocks measurable business value. 
• Guide multi-disciplinary squads (product, research, engineering, and customer success) from discovery through full production rollout. 
• Shape platform roadmap with field feedback, driving features that accelerate time-to-value and differentiate JazzX in the market. 

You are equally comfortable white-boarding LLM retrieval strategies, optimising prompt chains, troubleshooting Kubernetes deployments, or presenting to a C-suite audience. 

Key Responsibilities 

Focus Area 

What You’ll Do 

Solution Architecture 

• Design end-to-end architectures that integrate JazzX’s AGI services (LLM orchestration, vector search, tool-calling agents) with client data sources, APIs, and security controls. 
• Define scalability, resilience, compliance, and observability patterns; set SLAs/SLOs for mission-critical services. 
• Lead technical design reviews and steer decisions on cloud, data, and AI frameworks. 

Technical Delivery & GTM Execution 

• Run the full delivery lifecycle—discovery, PoC, pilot, production, and hyper-care—balancing speed with robust engineering practices. 
• Establish repeatable deployment playbooks that field teams can apply across industries. 

Client Engagement & Stakeholder Management 

• Translate business problems into AGI solutions, articulate trade-offs, and build trusted-advisor relationships with technical and non-technical leaders. 
• Deliver roadmap briefs, architecture artefacts, and demo sessions; manage risk, scope, and timeline. 

Technical Leadership & Mentorship 

• Coach engineers across JazzX in AGI best practices, code quality, security, and DevOps. 
• Foster a culture of experimentation and continuous learning; lead internal guilds on LLM optimisation and MLOps. 

Innovation & Platform Influence 

• Evaluate emerging AI/ML and tooling (e.g., AutoGen, RAG pipelines, WASM inferencing) and pilot them in customer contexts. 
• Feed field insights back to product and research teams to prioritise new capabilities. 

Qualifications 

Must-Have 

• 10–12 years of software engineering experience, 5+ in staff/principal or solution-architect roles. 
• Proven record delivering large-scale, low-latency distributed systems (Python, Java, Go, or C++). 
• Hands-on with LLM / AI frameworks (LangChain, LlamaIndex, PyTorch, TensorFlow) and productionising ML pipelines. 
• Expertise integrating REST/GraphQL APIs, streaming platforms (Kafka), SQL & NoSQL stores, and vector DBs. 
• Outstanding client-facing communication, executive-level presentation, and stakeholder-management skills. 

Nice-to-Have 

• Masters or PhD in AI/Data Science/Computer Science 
• Experience shipping RAG or agent-based AI systems in regulated industries. 
• Nice to have certifications in cloud architecture, data engineering, or security (e.g., AWS SA-Pro, CKA). 
• Background in professional-services, forward-deployed engineering, or AI platform product management. 

Attributes 

• Empathy & Ownership: You listen carefully to user needs and take full ownership of delivering great experiences. 
• Startup Mentality: You move fast, learn quickly, and are comfortable wearing many hats. 
• Detail-Oriented: You care about the little things  
• Mission-Driven: You want to solve important, high-impact problems that matter to real people. 
• Team-Oriented: Low ego, collaborative, and excited to build alongside highly capable engineers, designers, and domain experts.  

Travel:

This position requires the ability to travel to client sites as needed for on-site deployments and collaboration. Travel is estimated at approximately 30–40% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities.