Specialist Solutions Architect - AI/ML
Databricks13 days ago
Bengaluru, IndiaSenior
Responsibilities
- Architect production-level ML and AI workloads for customers on the Databricks platform.
- Design and advise on GenAI solutions including RAG architectures, agentic systems, tool-calling and multi-agent orchestration, guardrails, natural-language querying, evaluation, observability, and monitoring.
- Build, scale, optimize, and productionize customer AI workloads using MLOps practices.
- Provide advanced technical support to Solution Architects across feature engineering, training, tracking, serving, and model monitoring during technical sales.
- Collaborate with product and engineering teams to represent customer needs, influence priorities, and drive adoption of Databricks AI offerings.
- Mentor colleagues and contribute to the broader ML subject-matter-expert community.
Requirements
- At least 5 years of hands-on industry ML experience.
- Experience as an ML Engineer building and maintaining production-grade cloud infrastructure for ML applications, including drift monitoring, or as an AI Engineer working with LLMs and agentic systems.
- Experience with vector databases, LLM fine-tuning, AI guardrail systems, and deploying LLMs using tools such as HuggingFace, Langchain, and OpenAI.
- Graduate degree in a quantitative discipline such as Computer Science, Engineering, Statistics, or Operations Research, or equivalent practical experience.
- Ability to communicate and teach technical concepts to both technical and non-technical audiences.
- Preferred: at least 2 years of customer-facing pre-sales or post-sales experience.
- Ability to meet technical training and role-specific outcome expectations within 3 months of hire.
- Ability to travel up to 30% as needed.
Benefits
- Hybrid work arrangement based in Bengaluru.
- Comprehensive benefits and perks, with details varying by region.
- Travel may be required up to 30%.
Tech Stack
Categories
Solutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.