AI Agent Engineer
Bengaluru, Karnataka, IndiaJobNo compensation foundPosted 1mo agoVerified open 5 days ago
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At a glance
Compensation
No compensation found
Location
Bengaluru, Karnataka, India
Work Authorization
Not specified
Job overview
The AI Agent Engineer designs, builds, and maintains LLM-powered agents and integrations, ensuring reliable workflows, cost‑effective model usage, and robust incident‑response automation for internal development and SRE teams.
Skills & qualifications
RequiredNice to have
Skills
Quality AssuranceOrchestrationJiraRESTArtificial IntelligenceStreamingPythonDatabase CachingPagerDutyGithubLLM APIsAnthropic ClaudeLangChainLlamaIndexDSPyCrewAIREST APIWebhook IntegrationSlackJira/LinearNotionBigQueryCachingPrompt Management
Qualifications
3+ Years Software Engineering Experience1+ Years LLM‑Powered Systems Experience
Full job description
Responsibilities:
- Agent Development: Build and maintain internal agents for PR review, issue triage, testing, go-live validation, customer calls, regression checks, incident response, anomaly detection, and post-mortem drafting. Design each agent with clear success metrics, feedback loops, monitoring, cost tracking, and kill criteria. Create reliable agent workflows with structured outputs, tool use/function calling, retries, fallbacks, and audit trails. Measure adoption, quality, false positives, latency, and time saved for every agent.
- Agent Platform and Integrations: Build integrations with GitHub, Slack, Jira/Linear, Notion, PagerDuty, CI/CD systems, and BigQuery. Own webhook/event-driven triggers for PRs, issues, deploys, alerts, and transcript availability. Create reusable patterns for prompt management, prompt versioning, evaluation datasets, and model selection. Keep LLM usage cost-disciplined through caching, routing by model tier, context management, and per-agent cost visibility.
- SRE AI Safety Net: Build incident response agents that query logs, deploy events, error spikes, and accuracy signals to generate first-line triage within minutes. Build post-mortem and anomaly detection agents using BigQuery-backed reliability data. Design safe runbook automation where irreversible production actions require human approval. Partner with SDET and DevEx engineers to define the quality bar and data foundation for SRE-AI workflows.
Requirements:
- 3+ years of software engineering experience with at least 1 year building production LLM-powered systems or agents used by real users.
- Strong Python engineering skills; ability to write maintainable, tested, production-quality services.
- Hands-on experience with LLM APIs, preferably Anthropic Claude, including tool use/function calling, structured outputs, streaming, prompt caching, and multi-turn context handling.
- Experience with at least one agent/orchestration framework such as LangChain, LlamaIndex, DSPy, CrewAI, or strong custom orchestration experience.
- Strong REST API and webhook integration experience across tools such as GitHub, Slack, Jira/Linear, Notion, PagerDuty, or similar.
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