6 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Build and deploy production-grade AI agents and multi-step orchestration workflows.
- Integrate agents with enterprise APIs, knowledge sources, business applications, databases, and automation platforms.
- Implement tool calling, workflow state, memory, human approvals, exception handling, and recovery mechanisms.
- Develop reusable services and APIs for safe agent interaction with enterprise systems.
- Apply authentication, authorization, data protection, audit logging, human oversight, and other responsible-AI and security controls.
- Implement automated testing for prompts, tools, integrations, workflows, security controls, and end-to-end agent behavior.
- Establish monitoring for quality, latency, cost, tool failures, model behavior, and production incidents.
- Build CI/CD pipelines and support releases, rollback, versioning, and environment management.
- Troubleshoot production issues and improve agent reliability and performance.
- Partner with Architecture to translate approved patterns and standards into deployable solutions.
Requirements
- 4–5 years of experience in software, cloud, integration, automation, or AI engineering.
- At least 1–2 years of hands-on experience deploying LLM or agentic applications into production.
- Strong Python development experience and working knowledge of APIs, event-driven integrations, and databases.
- Experience with an agent framework or platform such as Agents SDK, LangGraph, LangSmith, Semantic Kernel, or AWS Bedrock.
- Experience implementing retrieval, tool calling, workflow orchestration, structured outputs, and human-in-the-loop processes.
- Practical experience with Git, automated testing, CI/CD, containers, and cloud deployment.
- Experience with production monitoring, logging, alerting, incident investigation, and performance optimization.
- Understanding of enterprise security, identity, secrets management, access controls, and sensitive-data protection.
- Ability to work across architecture, security, platform, and business teams.
- Preferred experience with Azure or AWS and infrastructure-as-code tools.
- Preferred familiarity with Kubernetes, serverless services, API gateways, message queues, or workflow platforms.
- Preferred experience evaluating agent quality, task completion, groundedness, tool selection, safety, latency, and cost.
- Preferred understanding of tracing and observability across prompts, models, tools, APIs, and workflow steps.
- Preferred experience integrating AI solutions with SharePoint, Salesforce, ServiceNow, Jira, or enterprise data services.
Tech Stack
Categories
About Brillio
Brillio is a privately held digital engineering and enterprise AI services firm that helps Fortune 1000 companies modernize products, data, and infrastructure. It combines consulting and managed services with an accelerator platform (ADAM) across cloud, AI, data engineering, customer experience, and infrastructure workstreams. Founded in 2014 and headquartered in Dallas, it operates delivery centers across North America, Europe, and Asia, with focus areas that include healthcare and life sciences.