Careers/Engineering
AI/ML Solutions Architect
Translate enterprise problems into production-grade AI, data and platform architectures. Partner with clients and product teams, own the technical blueprint, and stay close enough to the code to be credible.
About the role
We are hiring an AI/ML Solutions Architect at the Staff level. This role owns the architectural bridge between enterprise customer problems and the systems our engineering teams build. You will sit in on early customer conversations, shape the technical design, and run point with our AI, data, and platform teams to make sure the delivered system matches the commitment.
You will work across RAG, agentic workflows, data platforms on Snowflake or Databricks, and ML infrastructure on Ray and vLLM. You are not a pre-sales presenter; you are an engineer who has earned the title through production scars, who can write the proof-of-concept, argue the tradeoffs, and hand a clean blueprint to the delivery team.
Responsibilities
Architecture & Design
- Own end-to-end architectures that span AI agents, RAG pipelines, data platforms and inference infrastructure.
- Design lakehouse and warehouse patterns (Snowflake, Databricks) that support both analytics and ML workloads.
- Define the agent / orchestration / retrieval layer for complex enterprise workflows with clear guardrails and evals.
- Produce reference architectures, blueprints and decision records that engineering teams implement.
Customer & Stakeholder Leadership
- Lead technical discovery with enterprise customers: map business processes to systems of record and systems of engagement.
- Translate requirements into system designs, with explicit tradeoffs on cost, latency, governance and change risk.
- Run architecture reviews with customer CTOs, platform leads and compliance stakeholders.
- Shepherd proposals through scoping, staffing and delivery hand-off without losing technical integrity.
Proof of Concepts & Delivery
- Build targeted proof-of-concepts to de-risk technical assumptions before engineering scale-out.
- Pair with delivery teams on critical design sessions, incident reviews and pre-production readiness checks.
- Validate that shipped systems meet the agreed SLOs, security posture and cost envelope.
- Capture learnings in an internal architecture knowledge base and level up other engineers.
Technical Direction
- Influence our roadmap of reference patterns, accelerators and reusable modules across AI, data and platform.
- Evaluate new frameworks, serving stacks and cloud services; publish recommendations with evidence.
- Partner with sales and product on which problems we take on and which we do not.
- Mentor senior engineers on architecture thinking, documentation and stakeholder communication.
Qualifications
Must-Have Technical Expertise
- 8+ years of engineering experience with a track record shipping production AI, ML or data-platform systems.
- Deep practical knowledge across at least two of: RAG architectures, agentic orchestration, ML platform (Ray, KubeRay), inference serving (vLLM, liteLLM), cloud data platforms (Snowflake, Databricks).
- Strong REST API design fundamentals and ability to review or write service contracts end-to-end.
- Hands-on with cloud platforms (GCP, AWS, or Azure): compute, storage, networking, IAM, security.
- Track record of leading architecture for multi-system production deployments with measurable business impact.
- Proficiency with AI-assisted development tools (Cursor, Claude Code, GitHub Copilot, or similar).
Leadership & Communication
- Proven comfort in customer-facing technical leadership: discovery, proposal, delivery oversight.
- Ability to write architecture decision records, design docs and review documents at a level senior engineers respect.
- Pragmatic judgement on build-vs-buy, simplicity-vs-flexibility, and time-to-value.
- Strong mentorship and cross-team influence without formal authority.
Preferred/Bonus
- Experience with Unity Catalog, MLflow, Delta Lake, or Snowpark at a meaningful scale.
- Prior role as Solutions Architect at an AI, data or cloud platform company (Databricks, AWS, Snowflake, Cloudera, HuggingFace).
- Public speaking, whitepaper or open-source architecture contributions.
- Experience with regulated industries (finance, healthcare) and the data governance tradeoffs they imply.
- Strong Vietnamese and English communication skills.
Benefits
- Competitive salary and performance incentives, scaled to staff-level responsibility
- Shape how Magnitudeminds engages with enterprise AI problems
- Work across the full stack: AI, data, platform, and customer strategy
- Flexible work arrangements
- A collaborative, innovative engineering team environment
Apply
Apply for AI/ML Solutions Architect.
Send a CV and a short note on what you have shipped. We read every application and reply to all of them.