L3 AI App Support Engineer

Synectics APAC; Hyderabad; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

Synectics APAC is hiring for an experienced AI/Software Engineer to provide advanced L3 support for GenAI applications and enhance Python-based AI services. You will troubleshoot RAG pipelines, integrate OpenAI API and AWS Bedrock, and work with LangChain/LangGraph and MLOps concepts.

You will diagnose issues across Azure and Kubernetes environments, optimize model training and deployment, and contribute to production releases. Strong debugging and independent problem-solving are required.

Qualifications

• 6+ years of software/AI engineering or related technical roles.
• Proficient Python development and debugging.
• Strong background in Generative AI, LLMs, RAG, and enterprise AI apps.
• Solid understanding of MLOps and LLMOps concepts.
• Hands-on with LangChain and LangGraph.
• Experience with OpenAI API and AWS Bedrock.
• Familiar with Azure/Kubernetes/AKS and search services.
• Observability using Datadog or Fiddler.
• Ability to fix defects at code level and improve architectures.
• Ability to work with limited documentation and drive solutions.

Responsibilities

• Provide advanced L3 support for AI/GenAI apps with debugging and RCA.
• Analyse and enhance Python-based AI applications and services.
• Troubleshoot RAG pipelines: retrieval, prompts, embeddings, orchestration.
• Integrate LLMs with OpenAI API and AWS Bedrock.
• Develop apps using LangChain and LangGraph.
• Work with Agentic AI tools to improve capabilities.
• Support model training, fine-tuning, evaluation, and optimization.
• Diagnose issues across Azure and Kubernetes/AKS environments.
• Leverage Azure Cognitive Search / Snowflake Cortex for knowledge retrieval.
• Monitor performance with Datadog/Fiddler and similar tools.
• Collaborate with teams to implement permanent fixes and reliability.
• Contribute to deployment, testing, and production releases.
• Create runbooks, docs, and knowledge-base content.
• Identify recurring issues and implement automation to reduce incidents.
• Contribute to MLOps and LLMOps practices including deployment and lifecycle.

Skills

Python development

Debugging

LLMs / Generative AI

MLOps / LLMOps

LangChain

LangGraph

OpenAI API

AWS Bedrock

Kubernetes / AKS

Azure AI / Cognitive Search

Observability tools (Datadog, Fiddler)

Code-level resolution

Tools

LangChain

LangGraph

OpenAI API

AWS Bedrock

Kubernetes/AKS

Azure AI/Search

Snowflake Cortex Search

Datadog

Fiddler

Job description

• Provide advanced L3 technical support for AI/GenAI applications, including complex debugging, root cause analysis, and code-level resolution.
• Analyse and enhance Python-based AI applications and backend services.
• Troubleshoot and improve RAG pipelines, including retrieval, prompt engineering, orchestration, embeddings, and response quality.
• Work on LLM integrations such as OpenAI API and AWS Bedrock.
• Develop, debug, and enhance applications using LangChain and LangGraph.
• Work with Agentic AI tools and architectures to improve AI application capabilities.
• Support model training, fine-tuning, evaluation, and optimization activities.
• Diagnose application and infrastructure issues across Azure and Kubernetes/AKS environments.
• Work with Azure AI Search/Cognitive Search and Snowflake Cortex Search for enterprise knowledge retrieval.
• Monitor application and model performance using Datadog, Fiddler, and similar observability tools.
• Collaborate with development, platform, and MLOps teams to implement permanent fixes and improve application reliability.
• Participate in release activities, code enhancements, performance improvements, and production deployments.
• Develop and maintain runbooks, troubleshooting guides, technical documentation, and knowledge-base content.
• Identify recurring issues and implement automation or engineering solutions to reduce incidents.
• Contribute to MLOps and LLMOps practices, including deployment, monitoring, model lifecycle, and operationalization.

Key Responsibilities

• Provide advanced L3 technical support for AI/GenAI applications, including complex debugging, root cause analysis, and code-level resolution.
• Analyse and enhance Python-based AI applications and backend services.
• Troubleshoot and improve RAG pipelines, including retrieval, prompt engineering, orchestration, embeddings, and response quality.
• Work on LLM integrations such as OpenAI API and AWS Bedrock.
• Develop, debug, and enhance applications using LangChain and LangGraph.
• Work with Agentic AI tools and architectures to improve AI application capabilities.
• Support model training, fine-tuning, evaluation, and optimization activities.
• Diagnose application and infrastructure issues across Azure and Kubernetes/AKS environments.
• Work with Azure AI Search/Cognitive Search and Snowflake Cortex Search for enterprise knowledge retrieval.
• Monitor application and model performance using Datadog, Fiddler, and similar observability tools.
• Collaborate with development, platform, and MLOps teams to implement permanent fixes and improve application reliability.
• Participate in release activities, code enhancements, performance improvements, and production deployments.
• Develop and maintain runbooks, troubleshooting guides, technical documentation, and knowledge-base content.
• Identify recurring issues and implement automation or engineering solutions to reduce incidents.
• Contribute to MLOps and LLMOps practices, including deployment, monitoring, model lifecycle, and operationalization.

Required Skills & Qualifications

• 6+ years of experience in software/AI engineering, application support, or a related technical role.
• Strong hands-on experience with Python development and debugging.
• Solid experience with Generative AI, LLMs, RAG, and enterprise AI applications.
• Strong understanding of MLOps and LLMOps concepts.
• Hands-on experience with LangChain and LangGraph.
• Experience with Agentic AI tools/frameworks and AI orchestration.
• Experience with LLM APIs, preferably OpenAI API and AWS Bedrock.
• Strong understanding of RAG architecture, embeddings, vector search, prompt engineering, and retrieval optimization.
• Experience with model training, fine-tuning, evaluation, and performance optimization.
• Hands-on experience with Microsoft Azure and Kubernetes/AKS.
• Experience with Azure AI Search/Cognitive Search and Snowflake Cortex Search.
• Experience with observability tools such as Datadog and Fiddler.
• Strong troubleshooting, debugging, analytical, and problem-solving skills.
• Ability to understand existing codebases, identify defects, and implement code-level solutions and enhancements.
• Ability to work effectively in environments with limited documentation and independently drive technical solutions.