Specialist Technical Support Engineer (AI Solutions)

So, what's the role all about?

As a Specialist Advanced Engineering Technical Support Engineer, you will provide senior-level L2/L3 engineering support for AI-powered solutions in production environments. This role combines deep troubleshooting expertise with software engineering capabilities, supporting agentic AI applications, cloud infrastructure, APIs, data platforms, and automation frameworks.

You will be responsible for diagnosing complex incidents, performing root-cause analysis, implementing code-level fixes, improving platform reliability, and partnering with architects, developers, and business stakeholders to ensure high availability and performance of critical AI solutions. 

How will you make an impact?

• Own and resolve complex P1/P2 incidents across agentic AI, cloud, data, and application layers.
• Diagnose and troubleshoot AI agent workflows, LLM integrations, RAG pipelines, APIs, MCP tools, and orchestration failures.
• Analyze Snowflake and AWS environments to identify performance, security, data, and integration issues.
• Perform code-level debugging, implement fixes, and develop regression tests for production issues.
• Monitor system health using observability and LLMOps tools, proactively identifying reliability risks.
• Support automation frameworks, event-driven workflows, and data pipelines to ensure consistent operations.
• Improve operational maturity through runbooks, alerts, knowledge articles, and continuous improvement initiatives.
• Collaborate with engineering, architecture, product, and business teams to drive successful AI solution adoption.
• Ensure governance, security, auditability, and safe execution of autonomous AI workflows. 

Have you got what it takes?

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
• 8-12 years of experience in Software Engineering, Platform Engineering, SRE, DevOps, Data Engineering, or Advanced Technical Support.
• Strong hands-on experience with Python development, SQL, REST APIs, and distributed systems.
• Experience supporting production applications in cloud environments, preferably AWS.
• Strong understanding of Snowflake data platform, query optimization, security controls, and data operations.
• Experience troubleshooting APIs, microservices, event-driven architectures, and workflow orchestration platforms.
• Hands-on experience with CI/CD pipelines, Git, testing frameworks, and automation practices.
• Knowledge of observability tools, logging, monitoring, tracing, and incident management.
• Experience with IAM, OAuth 2.0, RBAC, secrets management, and enterprise security practices.
• Excellent problem-solving, communication, and stakeholder management skills. 
• Experience with Agentic AI frameworks such as LangGraph, LangChain, PydanticAI, AutoGen, CrewAI, or Semantic Kernel.
• Hands-on experience with LLM platforms including OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Snowflake Cortex, or Google Gemini.
• Experience with MCP (Model Context Protocol) implementations and AI tool integrations.
• Knowledge of RAG architectures, embeddings, vector databases, and AI evaluation frameworks.
• Experience with Snowflake Cortex Agents, Cortex Search, Cortex Analyst, and Snowpark.
• Experience supporting AWS services such as Lambda, ECS/Fargate, Step Functions, EventBridge, SQS/SNS, API Gate