Salary
≈ $14k – $32k per year (Estimated)
Location
Hybrid (Bengaluru, Mumbai, India)
Experience
2+ years exp
First seen by Alion on Oct 27, 2026.
Overview
Company
Impact
Profile match
IDFC FIRST Bank is an Indian private sector universal bank headquartered in Mumbai, offering savings and current accounts, deposits, home, personal, vehicle and small business loans, credit cards, forex, payments and wealth management to retail, small business and corporate customers. It was formed in 2018 through the merger of IDFC Bank and Capital First, operates a nationwide branch network and runs retail, wholesale and other banking segments, with large technology teams in Bengaluru, Chennai and Mumbai. It hires software engineering managers, backend developers, data scientists and engineers, AI and MLOps engineers, QA and DevOps engineers, credit risk analysts and product heads.
Backed by Warburg Pincus
Responsibilities:
- Design, build, and scale production-grade AI solutions at IDFC FIRST Bank to drive measurable business impact.
- Own solutions end-to-end, from coding to deployment, governance, and cross-functional delivery.
- Translate business problem statements into production-grade AI solutions with end-to-end ownership from discovery to deployment and monitoring.
- Build, deploy, and maintain scalable AI/ML systems with strong engineering, reliability, and governance standards.
- Engage stakeholders to define scope, assess data readiness, and identify the most effective solution approach.
- Plan milestones, manage timelines, and drive initiatives from concept through delivery.
- Implement responsible practices, including validation frameworks, guardrails, and compliance controls.
- Communicate progress, risks, trade-offs, and outcomes clearly to senior leadership.
- Stay current with emerging models, frameworks, and techniques and apply relevant innovations.
- Collaborate cross-functionally with business, engineering, data, and risk teams to deliver enterprise-ready solutions.
Key Success Metrics:
- Correct selection of AI approach (rules, AI, or hybrid) for the problem on first implementation.
- Models achieving agreed performance benchmarks and measurable business impact.
- Stable, reliable production systems with minimal drift and fast issue resolution.
- Cost-effective scalability as data, usage, and complexity grow.
- Compliance with security, privacy, and regulatory standards with no critical incidents.
- Clear stakeholder understanding of solution capabilities, risks, and limitations.
Skills
AI, Artificial Intelligence, Data Science, Data Scientist, Gen AI, Generative AI, LLM, Large Language Model, ML, Machine Learning
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