The Role

We are looking for a Senior Solution Architect who is a genuine technical generalist: someone who reasons from first principles, is insatiably curious about how things work under the hood, and can move fluidly between low-level implementation detail and high-level business narrative. You will own the technical shape of diverse client engagements - from cloud and full-stack platforms to modern AI and inference systems - and remain hands-on through delivery rather than handing designs over the wall.

This is a role for a builder-architect: equally comfortable whiteboarding a system with a principal engineer, debugging an inference bottleneck, or explaining a trade-off to a customer and internal teams in plain language.

What Youll Do

Own end-to-end solution architecture for client engagements across cloud, data, full-stack, and AI/ML workloads, balancing technical rigour with cost, security, and time-to-value.
Design from first principles - decompose unfamiliar problems, evaluate options on their merits, and justify decisions rather than defaulting to patterns or hype.
Stay hands-on through delivery: prototype, review code and infrastructure, unblock engineering teams, and ensure what was designed is what actually ships.
Simplify complex technical concepts for business, leadership, and customer audiences - translate architecture into outcomes, risks, and options stakeholders can act on.
Lead client conversations, discovery workshops, and solution presentations; act as a trusted technical advisor and the bridge between engineering and the business.
Architect AI-centric solutions - reason about model selection, inference architecture, tuning/optimization, and the systems that serve models in production.
Coach and uplift teams - mentor engineers and associate architects, run design reviews, and raise the technical bar through teaching, not gatekeeping.
Explore and prototype emerging technologies, bringing a spirit of creative, spontaneous problem-solving to engagements where the right answer isnt yet obvious.

Core Technical Competencies

You should bring a strong working foundation across the following - breadth as a generalist, with the ability to go deep wherever a problem demands it:

System design fundamentals - scalability, reliability, data modelling, consistency, latency, and the trade-offs between them.
Cloud architecture and services - ideally AWS - including compute, storage, networking, serverless, and well-architected design principles.
Full-stack development - backend and frontend, APIs, and the ability to read, write, and review production code with credibility.
Software engineering best practices - version control, testing, design patterns, and maintainable, observable systems.
DevOps and platform engineering - CI/CD, IaC, containerization, orchestration, and operational concerns across the delivery lifecycle.

AI Inference Systems

A solid, current understanding of how modern AI systems are built and operated - not just how to call an API:

Underlying architecture of AI systems and inference pipelines - how models are served, scaled, and integrated into broader applications.
Model lifecycle fundamentals - how model development, fine-tuning, and optimization work, and when each is appropriate.
Practical grasp of inference economics and performance - latency, throughput, cost, quantization, and the levers that move them.
Familiarity with GenAI patterns - retrieval-augmented generation, agentic workflows, evaluation, and grounding/guardrails.

Who You Are

Beyond the skills, were looking for a particular mindset:

A first-principles thinker who questions assumptions and reasons up from fundamentals rather than relying on received wisdom.
A curious generalist and technology enthusiast with a genuine drive to understand how things work under the hood.
A creative, spontaneous problem-solver - comfortable improvising, prototyping, and finding non-obvious paths when the textbook answer falls short.
A clear communicator who is well-spoken and equally effective with deeply technical engineers and non-technical executives.
A natural teacher - someone who enjoys explaining, simplifying, and helping others level up.
Strong attention to detail paired with the judgment to know when to zoom out to the bigger picture.

Experience Qualifications

6-8 years of professional experience, with a strong foundation as a software developer/engineer.
Demonstrated progression into solution architecture - associate, and ideally senior-associate level, exposure.
A track record of delivering technical solutions in client-facing or product environments.
Bachelors degree in Computer Science, Engineering, or equivalent practical experience.
Relevant cloud certifications (e.g., AWS Solutions Architect) are a strong plus.

Nice to Have

Prior consulting or professional-services delivery experience.
Hands-on experience with Bedrock, SageMaker, or comparable ML/GenAI platforms.
Experience presenting at workshops, enabling teams, or producing technical thought-leadership content.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Senior Solution Architect

Job Description

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