About Soulpage :

Soulpage IT Solutions is an AI/ML consulting, services, and product development company. We design and ship production-grade AI systems for enterprise and government clients from agentic architectures and LLM platforms to data-intensive applications, while also building our own products. We work hands-on across the modern AI stack and pride ourselves on shipping scalable, reliable, well-engineered solutions.

Role :

We are looking for a Principal Solutions Architect to lead our AI practice end to end. This is a senior, hands-on leadership role for someone who can sit in front of a client, translate ambiguous business problems into a solution architecture, guide a team of AI engineers to deliver it, and stand behind the quality, scalability, and risk posture of what we ship. You will own the technical direction of our AI engagements agentic systems, LLM, and generative-AI applications and be the bridge between clients and the engineering team. You should be equally comfortable whiteboarding an architecture with a client's CTO, reviewing an agent pipeline with an engineer, and making the call on the right model, cloud, and design pattern for the job.

What You'll Do :

Client engagement & requirements :

- Act as the primary technical point of contact for clients across discovery, scoping, and delivery.

- Run requirement-gathering sessions, ask the right questions, and convert business needs into clear technical scope, estimates, and proposals.

- Communicate complex AI concepts clearly to both technical and non-technical stakeholders, and manage expectations through the project lifecycle.

- Support pre-sales : solution shaping, effort estimation, SOWs, and technical demos.

Solution architecture :

- Design solution architectures for agentic, LLM, and generative-AI systems multi-agent orchestration, RAG, tool use, evaluation, and human-in-the-loop workflows.

- Make and justify build decisions : model selection (OpenAI, Anthropic Claude, open and self-hosted models), cloud (Azure, AWS), data stores, orchestration frameworks, and integration patterns.

- Architect for scale, performance, cost, and reliability from day one not as an afterthought.

- Define reference architectures, patterns, and reusable components the team can build on.

Team leadership & delivery :

- Lead, mentor, and grow a team of AI/ML and full-stack engineers.

- Set engineering standards and enforce best practices : code quality, testing, evaluation, observability, and documentation.

- Champion AI-assisted development drive effective, disciplined use of tools like Claude Code and Codex (OpenAI) to raise delivery velocity while keeping engineers focused on validation, testing, and review.

- Review architecture and key implementations; unblock the team and own delivery outcomes.

Quality, monitoring & enterprise AI risk :

- Establish monitoring, evaluation, and observability for AI systems in production (quality, latency, cost, drift, hallucination, regression).

- Own the risk posture of enterprise AI solutions : data privacy and security, access control, prompt and model safety, governance, auditability, and compliance considerations.

- Build guardrails and evaluation frameworks so quality and safety are measurable, not anecdotal.

What We're Looking For :

Must-have :

- Proven experience designing and delivering production AI/ML or generative-AI systems, with at least some of that in a client-facing or consulting context.

- Deep, hands-on knowledge of agentic architectures, LLMs, and the generative-AI stack (RAG, orchestration, tool use, prompt and context engineering, evaluation).

- Strong cloud experience on Azure and AWS, including AI/ML services and deployment.

- Practical experience with OpenAI and Anthropic Claude APIs and ecosystems.

- Effective, real-world use of AI coding tools Claude Code and Codex as part of the delivery workflow.

- Solid software engineering foundations : scalable system design, high-performance and cost-efficient solutions, and engineering best practices.

- Working knowledge of monitoring, evaluation, and the risk/governance considerations of enterprise AI.

- Excellent communication and stakeholder-management skills clear, confident, and credible with clients.

- A dynamic, adaptable, ownership-driven mindset; comfortable with ambiguity and fast-moving requirements.

Good to have :

- Experience with multi-agent frameworks and production agent pipelines.

- Experience with enterprise, regulated, or government clients and their constraints (security, on-prem / air-gapped, compliance).

- Experience leading a team or practice and setting technical standards.

- Familiarity with data engineering, MLOps/LLMOps, vector databases, and CI/CD.

- A track record of taking products or platforms from prototype to scale.

Why Join Us :

- Lead the AI practice of a focused, hands-on AI/ML company real ownership, not a title.

- Work across a varied portfolio of enterprise and product engagements on the latest AI stack.

- Shape how an AI services company builds including our standards for AI-assisted development.

- Direct access to leadership and the chance to influence company direction.