Vegapay
Forward Deployed Engineer
- Location
- Bengaluru
- Work mode
- Onsite
- Experience
- 2–3 yrs exp
- Pay
- ₹12–22 LPA (Est.)
- Type
- Full-time job, AI & ML
- Added
- 14 November 2026
About this role
Vegapay builds configurable fintech infrastructure that lets banks, NBFCs and enterprises launch and manage credit and payment programs. This full-time Forward Deployed Engineer role in Bengaluru works directly with bank and fintech partners on live credit card, UPI, lending, rewards, ledgering and reconciliation programs. Day to day, the engineer diagnoses production issues, ships scoped code fixes through a bank-grade change process, and builds AI agents using LLMs and RAG to triage escalations and automate recurring fixes. The role also covers AI guardrails, evaluation and monitoring, post-incident RCAs, and feeding field learnings back into the product. It suits engineers with 2–3 years of production experience in fintech or SaaS who have already built agentic AI workflows.
Vegapay is hiring for Forward Deployed Engineer, a full-time role based in Bengaluru (onsite).
Who can apply: 2–3 yrs exp. Skills: Python, SQL, LLMs, RAG, LangGraph, Kubernetes.
Hirastra checked that this opening is live. Apply directly through the official posting; applying is always free.
What you'll do
- Work with bank partners and internal teams to understand workflows and define success metrics
- Own problem-solving for live credit, UPI, lending and reconciliation programs, resolving escalations within SLAs
- Build and deploy LLM, RAG and tool-calling agents that triage issues, draft RCAs and automate fixes
- Ship tested production code changes with code review, audited commits and rollback plans
- Build guardrails, evaluation and observability for AI agents in a regulated setting
- Lead post-incident RCAs and turn one-off fixes into reusable platform patterns
What you need
- 2–3 years of software engineering experience in B2B SaaS, fintech or payments, including AI/ML work
- B.E./B.Tech in Computer Science or AI & ML with strong DSA fundamentals
- Proficiency in Python, TypeScript, Java or Go
- Hands-on experience with LLM APIs, RAG, embeddings and tool calling, with at least four agentic workflows built or operated in production
- Strong SQL, API knowledge (REST, JSON-RPC, GraphQL), observability tools, system design basics, a cloud platform and Kubernetes
- Ability to handle multiple high-pressure bank escalations with clear communication
Skills
- Python
- SQL
- LLMs
- RAG
- LangGraph
- Kubernetes
"Est." = Hirastra's estimate based on market data, not an official figure.
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