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.