Specialist Solutions Architect - AI/ML
Architect and deliver production AI/ML and generative AI solutions for Databricks customers, supporting technical pre-sales and scalable MLOps implementations. Requires 5+ years of ML or AI engineering experience, cloud expertise, and strong communication skills.
About the job
Responsibilities
- Design and deploy production-level machine learning and artificial intelligence architectures using the Databricks unified platform, including AI agents, end-to-end pipeline automation, and model training and inference optimization.
- Implement enterprise generative AI solutions, including Retrieval-Augmented Generation (RAG), tool calling, multi-agent orchestration, guardrails, AI evaluation, and observability systems.
- Build and maintain scalable customer AI workloads using MLOps practices across diverse industry domains.
- Partner with Solutions Architects during the sales cycle to guide prospects through feature engineering, model tracking, serving, and monitoring.
- Translate customer feedback into actionable product insights by collaborating with Engineering and Product teams.
- Mentor peers and contribute as a technical thought leader in the AI community.
Requirements
- 5+ years of hands-on industry experience in ML engineering or AI engineering.
- Experience building and maintaining cloud infrastructure supporting production ML applications and drift monitoring using AWS, Azure, or Google Cloud.
- Experience with LLMs and agentic systems, including vector databases, fine-tuning, AI guardrails, and frameworks such as LangChain, Hugging Face, or OpenAI APIs.
- Ability to explain complex AI and ML concepts to technical and non-technical audiences.
- Understanding of modern lakehouse architectures, Delta Lake, data modeling, and BI integration across major cloud platforms.
- Strong collaboration, continuous learning, and business-value orientation.
- Ability to travel up to 30% for customer engagements.
- Ability to meet role-specific training and technical delivery milestones within the first six months.
Preferred Qualifications
- Prior experience in a pre-sales or post-sales technical consulting role.
- Graduate degree in Computer Science, Engineering, Statistics, or a related quantitative field, or equivalent practical experience.
Compensation
- Local pay range: $180,000–$247,500 USD.
- Total compensation may also include an annual performance bonus, equity, and benefits.
Skills
Machine Learning, Artificial Intelligence, Generative AI, LLMs, MLOps, AWS, Azure, GCP, RAG, Vector Databases, LangChain, Hugging Face, Openai Apis, Delta Lake, AI Agents
Similar jobs
Solutions Architecture jobs
Databricks
United States
Leads enterprise customers through data engineering and data warehousing transformations, designing lakehouse architectures, production pipelines, migrations, and technical proofs of concept. Requires 5+ years of technical experience, strong Spark and SQL expertise, cloud-platform knowledge, and customer-facing consulting ability.
Wispr Flow
San Francisco, CA
Forward Deployed Engineers lead production deployments for customers, working across APIs, integrations, identity, data, and customer environments from discovery through adoption. The role requires customer-facing production software experience, broad technical depth, and strong communication.
Databricks
United States
Provides customer-facing technical leadership for secure, scalable Databricks deployments on AWS, covering architecture, networking, identity, platform administration, and infrastructure automation. Requires 5+ years of technical experience, customer-facing expertise, and strong cloud and data-platform skills.
Cape
Arlington, VALeads technical engagements, deployments, and integrations for federal customers, partnering across product, engineering, and business development. Requires networking expertise, deployment automation, defense or telecommunications experience, active TS/SCI clearance, and substantial travel.
Kombo
New York, NY
Founding US Solutions Engineer owning technical customer relationships across pre-sales and post-sales, from discovery and architecture design through implementation and go-live. Requires 4+ years in technical customer-facing B2B SaaS roles, hands-on API experience, and strong stakeholder communication.