2 days ago
Pune, IndiaSenior / Staff+
Responsibilities
- Own and resolve complex P1/P2 incidents across agentic AI, cloud, data, and application layers.
- Diagnose AI agent workflows, LLM integrations, RAG pipelines, APIs, MCP tools, and orchestration failures.
- Analyze Snowflake and AWS environments for performance, security, data, and integration issues.
- Perform code-level debugging, implement production fixes, and develop regression tests.
- Monitor system health with observability and LLMOps tools and identify reliability risks.
- Support automation frameworks, event-driven workflows, and data pipelines.
- Create runbooks, alerts, knowledge articles, and continuous-improvement initiatives.
- Collaborate with engineering, architecture, product, and business teams on AI solution adoption.
- Ensure governance, security, auditability, and safe execution of autonomous AI workflows.
Requirements
- 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.
- Hands-on experience with Python, SQL, REST APIs, distributed systems, cloud production applications, Snowflake, APIs, microservices, event-driven architectures, workflow orchestration, CI/CD pipelines, Git, testing frameworks, automation, observability, and incident management.
- Experience with IAM, OAuth 2.0, RBAC, secrets management, and enterprise security practices.
- Experience with agentic AI frameworks such as LangGraph, LangChain, PydanticAI, AutoGen, CrewAI, or Semantic Kernel.
- Experience with LLM platforms including OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Snowflake Cortex, or Google Gemini.
- Experience with MCP implementations, AI tool integrations, RAG architectures, embeddings, vector databases, and AI evaluation frameworks.
- Experience with Snowflake Cortex Agents, Cortex Search, Cortex Analyst, Snowpark, and AWS services including Lambda, ECS/Fargate, Step Functions, EventBridge, SQS/SNS, API Gateway, and CloudWatch.
- Familiarity with Airflow, Temporal, dbt, ServiceNow, or Jira Service Management.
- Exposure to AI guardrails, governance frameworks, and secure autonomous workflows.
- Strong problem-solving, communication, and stakeholder management skills.
Benefits
- Work on next-generation AI-powered solutions alongside AI architects, engineers, and business leaders.
- Access to challenging projects, career advancement opportunities, continuous learning, and a collaborative technical environment.
- NiCE-FLEX hybrid work model with two days in the office and three days remote each week.
Categories
About NICE
NICE builds cloud contact center platforms, customer analytics, and workforce optimization tools for enterprises and public sector agencies, including public safety recording. Its portfolio includes CXone (CCaaS), digital self-service, interaction recording, RPA, and financial crime and compliance solutions through NICE Actimize. Founded in 1986 and headquartered in Hoboken, New Jersey, NICE is a public company traded on NASDAQ under the ticker NICE, serving customers in 150+ countries.