Specialist Technical Support Engineer (AI Solutions)

Overview

Senior-level L2/L3 engineering support for AI-powered solutions in production environments, combining deep troubleshooting with software engineering across agentic AI, cloud infrastructure, APIs, data platforms and automation frameworks.

What you'll do

• 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.

What you'll need

• 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.

Nice to have

• 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 Gateway and CloudWatch.
• Familiarity with Airflow, Temporal, dbt or other enterprise orchestration platforms.
• Experience with ServiceNow or Jira Service Management.
• Exposure to AI guardrails, governance frameworks and secure autonomous workflows.

Details

• Location: Pune, India.
• Work mode: NiCE-FLEX hybrid model, 2 days in the office and 3 days remote each week.
• Individual contributor role reporting into Technical Manager / AI Engineering Leader.