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Senior ML & AI Technical Solutions Engineer

Databricks
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BengaluruPosted 3mo ago

About the role

Senior technical solutions engineer focusing on debugging and maintaining GenAI and ML workloads on the Databricks platform, with emphasis on agents, vector search, model serving, and collaboration across engineering and account teams.

Responsibilities

  • Act as senior technical solution expert for complex issues spanning data pipelines, ML pipelines and/or AI applications, applying deep expertise in distributed systems.
  • Analyse and troubleshoot production workloads at the code level, optimise for performance, reliability, latency, and cost.
  • Diagnose and support Machine Learning and/or Large Language Model deployments, including real-time and batch inference, autoscaling, monitoring, logging, and alerting. Serve as a Subject Matter Expert guiding customers on experiment tracking, model registry, versioning, evaluation, labelling, tracing, and lifecycle observability.
  • Provide high-quality support by guiding customers in leveraging Databricks AI to solve generative AI use cases & challenges, leveraging LLMs, MCP, AI Agents, RAG/Agentic RAG, APIs, vector embeddings, semantic search, Vector Search/Lakebase databases, context orchestration, memory management, and prompt engineering.
  • Collaborate with internal teams to influence roadmap, product improvements and support business growth.
  • Develop expertise in productionizing systems in Databricks and share knowledge via wikis, technical documentation, and teaching AI systems new skills for internal/external use.

Qualifications

  • 8+ years of experience designing, building, and scaling Data, Machine Learning, and AI systems on-premises and in the cloud using Python, Scala, and Java in production environments, with expertise in Machine Learning and/or generative AI.
  • Experience with cloud platforms (AWS, Azure, or GCP); familiarity with Databricks is a plus.
  • Proficient in data engineering for end-to-end ML training pipelines, ideally with large datasets and Apache Spark.
  • SME knowledge in feature engineering, ML frameworks, model training, model monitoring, drift detection, and retraining strategies. Proficiency in algorithms, deep learning, and NLP techniques.
  • Prior experience building, designing or troubleshooting LLM-based Generative AI applications. Familiarity with agentic frameworks (e.g., LangChain, LangGraph). Expertise in context orchestration, prompt design, memory management, retrieval systems, vector embeddings, semantic search, and tool integrations.
  • Comprehensive knowledge of MLOps and LLMOps with expertise in model evaluation, scoring, ranking, optimisation, training, validation, and packaging.
  • Experience developing agent skills, plugins, and debugging with native AI capabilities is a plus.
  • Prior customer-facing experience is not required but desirable to develop excellent customer service skills.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience). Professional certifications are good to have.

Skills

Required:PythonScalaJavaCloud platformsLLM/Generative AI
Nice to have:Apache SparkAgent frameworks
Last updated Sep 10, 2026. Interested? Apply on the company site.

About Databricks

Leading Data and AI Platform for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

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