Staff AI Engineer, Agentic AI for Finance
Everpure (formerly Pure Storage) (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 50–90 LPA
Posted 3h ago
Reach people at Everpure (formerly Pure Storage)
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Everpure (formerly Pure Storage) you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead development and deployment of autonomous agent systems and enterprise platforms to automate financial workflows at scale.
- Architect resilient, auditable multi-agent workflows and secure data retrieval pipelines within a regulated finance environment ensuring SOX compliance.
- Establish operational excellence including automated evaluations, release gates, real-time observability, and provide technical mentorship across teams.
Minimum Requirements
- Proven experience designing and operating production-grade agentic AI or LLM systems with distributed architectures.
- Strong skills in Python, TypeScript, SQL, API development (FastAPI/GraphQL), and AWS cloud infrastructure including Docker and CI/CD.
- Experience with security and compliance controls for regulated environments: role-based access, audit logging, human-in-loop governance, and AI security standards.
- Location requirement: Must work from Bangalore office as per company policy; remote work only for approved leave or travel.
Ideal Candidate Profile
- Experienced technical leader able to translate complex AI architectures into business context for finance stakeholders.
- Skilled in integrating multi-disciplinary teams including product, engineering, and external partners in regulated enterprise settings.
- Focused on operational reliability, security, and compliance within autonomous AI systems in a finance or similarly regulated domain.