GDB/X - Senior Agentic AI Engineer (M/F/D)

Benefits

Parental leave

8 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

8 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

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Verification

Source-linked checked Jun 7, 2026

Salary

Not verified

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

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Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

GDB/X - Senior Agentic AI Engineer (M/F/D) Country / Location India Senior Agentic AI Engineer OrgCode: GDB/X Product Team: Intelligent Automation Responsibilities: - Engineer Core Components: Lead the development of the orchestration service and Agent-to-Agent (A2A) bus, writing high-performance Python code that routes thousands of requests per minute. - Build Complex Agents: Implement "Horizon 3/4" autonomous agents (e.g., self-correcting coding agents, complex supply chain optimizers) using LangGraph or AutoGen hosted on AKS. - Integrate Data & AI: Build robust integrations between Databricks (Unity Catalog) and our agent runtime, ensuring agents have access to real time, governed business data. - Optimize Performance: Tackle the hard problems of agentic AI-latency reduction, token cost optimization, and managing distributed state across long-running workflows. - Mentor & Review: Conduct code reviews for junior engineers and divisional teams, ensuring that all agent code adheres to our Zero-Trust security practices and software engineering standards. - Develop Tools (MCP): Build and maintain a library of Model Context Protocol (MCP) compliant tools that allow agents to interact with SAP, ServiceNow, and other enterprise APIs. Qualifications: - Engineering Mastery: You are a software engineer first. You write clean, testable, production-grade Python (FastAPI, Pydantic) and are comfortable with async/await patterns and concurrency. - Container Native: You don't just run Docker locally; you have experience deploying and debugging complex appl

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