ANSR is hiring for one of its clients. About American Airlines:
To Care for People on Life's Journey®. Together with our American Eagle regional partners, we offer thousands of flights daily to more than 350 destinations in more than 60 countries.
American Airlines is transforming the way it delivers technology to its customers and team members worldwide.
American’s Tech Hub in Hyderabad, India, is our latest technology office location and home to team members who drive technical innovation and engineer unrivalled digital products to best serve American’s customers and team members. With U.S. tech hubs in Dallas-Fort Worth, Texas and Phoenix, Arizona, our new team in Hyderabad, India enables better support of our 24/7 operation and positions American to deliver industry-leading technology solutions that create a world-class customer experience.

Engineer | AI Governance & Safety (IC)
Location: Hyderabad, India (Hybrid)

Role Summary:
As an Engineer in the AI Governance & Safety team at American Airlines, you will build and maintain AI agents and analytics/reporting solutions that support enterprise AI governance operations. This role leans toward data/analytics and applied AI engineering (analysis-heavy) rather than pure software engineering. You will develop Python + SQL solutions to generate governance and risk reports , publish insights via Power BI/Tableau dashboards , and support an internal Enterprise Agent Enablement Layer that powers governance agents.

Key Responsibilities:
Governance Reporting, Metrics & Dashboards:
Build and maintain enterprise governance dashboards in Power BI or Tableau , including semantic models, drilldowns, and refresh reliability.
Define and implement governance KPIs (e.g., governance coverage, review cycle time, risk ratings, control adherence, exceptions, approvals, remediation tracking etc).
Deliver recurring governance reporting (weekly/monthly/quarterly) with stakeholder-ready narratives and summaries.

Agent Development for Governance Automation:
Develop and maintain AI agents that support governance workflows: proposal review assistance , evidence aggregation, risk assessment facilitation, and automated report generation.
Build agent workflows using agent frameworks such as LangGraph and/or Copilot Studio agents (or equivalent) with strong attention to traceability and auditability .
Ensure agent outputs are consistent, reproducible, and governance-ready (structured outputs, evidence references, versioning where applicable).

Data & Backend Engineering (SQL + Python):
Write advanced SQL to curate datasets and generate insights.
Build Python backend services/APIs to orchestrate agent workflows, manage inputs/outputs, and integrate with internal systems.
Apply engineering fundamentals: testing, documentation, secure handling of sensitive data, logging/monitoring.

Platform & Workflow Integration (Tool-agnostic):
Integrate with an enterprise risk assessment & governance workflow platform to ingest/export governance artifacts and workflow status.
Contribute to the internal Enterprise Agent Enablement Layer .

Regulatory & Compliance Awareness
Demonstrate awareness of AI/data regulations and internal controls (e.g., GDPR , EU AI Act , and similar).
Support privacy-by-design and governance-by-design principles (data minimization, access controls, audit trails).

Required Qualifications

• 3–6 years of experience in Data Science, AI Engineering, analytics, data engineering or related roles.
• Strong SQL (advanced querying + optimization) and strong Python (backend services/APIs, automation).
• Experience with Power BI or Tableau (dashboarding, semantic modeling, KPI implementation).
• Cloud exposure in Azure or AWS
• Working understanding of AI/ML concepts and LLM-based agentic workflows
• Awareness of AI/data regulations (GDPR, EU AI Act, etc.) and practical implications.
• Candidates must have hands-on experience building AI agents using at least one enterprise-grade agent framework (e.g., Lang Graph or Copilot Studio agents , or equivalent) including tool invocation, orchestration, and structured outputs.

Regular Stakeholders / Key Interfaces You will work closely with:
AI Governance & Safety leadership (governance reporting, metrics, policy alignment)
Enterprise Risk & Compliance / Audit (risk assessments, controls, evidence readiness)
Legal & Data Privacy (AI Regulation interpretation, data handling obligations)
Information Security (access controls, secure integrations, sensitive data protection)
Enterprise Data & BI teams (data sources, semantic models, BI governance standards)
AI/ML platform & engineering teams (agent enablement layer integration, tooling standards)
Business owners of AI use cases (intake needs, governance review workflows, operational reporting)

Behavioral Competencies:
Analytical rigor: Translates ambiguous governance needs into measurable definitions, datasets, and insights.
Strong ownership: Drives work end-to-end; anticipates risks and resolves proactively.
Structured communication: Communicates clearly with both technical and non-technical stakeholders.
Quality & audit mindset: Builds solutions that are reproducible, traceable, and documentation ready.
Comfort with ambiguity: Iterates quickly and adapts as governance needs evolve.
Collaboration: Works effectively across risk, legal, privacy, security, data, and engineering.
Integrity & judgment: Handles sensitive information responsibly and escalates concerns early.
Minimum Education: BS/BE/BTech in Computer Science, Engineering, AI/ML, Data Science, or related field

Disclaimer : This job description outlines the general nature and key responsibilities of the role. It is not intended to be an exhaustive list, and responsibilities may be added, removed, or revised at any time in response to business, operational, or organizational requirements.