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Salary
≈ $23k – $50k per year (Estimated)
Location
Hybrid (Bengaluru, India)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Sep 25, 2026. Finastra scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Finastra is a financial technology company created in 2017 by merging the British firm Misys with the Canadian company D+H, bringing together several decades of banking software under one owner. Its products span retail and corporate core banking, payments processing, lending and syndicated loan servicing, treasury and capital markets systems, and it operates an open platform that lets third-party developers build applications against those cores. Headquartered in London and owned by Vista Equity Partners, it serves thousands of financial institutions and has been divesting parts of its portfolio to concentrate on lending and payments.

Who are we?

At Finastra, we’re a global leader in financial services software, dedicated to expanding access to financial services and shaping what’s next for the industry. Our technology powers mission-critical solutions across Lending, Payments and Universal Banking, supporting over 7,000 customers, including 80% of the world’s top 50 banks, in more than 110 countries.

What will you contribute?

We are seeking a motivated Senior AI Engineer to design, implement, and deploy cutting-edge AI solutions powered by large language models (LLMs).

Responsibilities & Deliverables

  • Develop key AI architecture patterns (RAG, text-to-sql, multi-agent, etc)
  • Create end-to-end production grade AI agents and integrate them into applications
  • Apply prompt engineering and context engineering techniques to optimize LLM performance
  • Implement function calling and tool use patterns for agentic workflows
  • Build and maintain AI workflows and pipelines using LangChain/LangGraph or equivalent
  • Deploy and manage LLM solutions on Azure OpenAI, AWS Bedrock, or similar cloud platforms
  • Implement observability and monitoring for AI systems to track performance, costs, and reliability
  • Automate model deployment and orchestration using CI/CD pipelines
  • Evaluate, benchmark, and document models

· Design and implement Model Context Protocol (MCP) integrations and tool orchestration frameworks for scalable agentic systems

· Build secure tool invocation and multi-system orchestration pipelines across enterprise services

· Implement security controls for AI systems, including data access governance, PII handling, and safe tool usage

· Ensure secure and compliant AI deployments aligned with enterprise and regulatory standards

Required Skills & Experience

  • Programming: Strong proficiency in Python for AI/ML development
  • LLM Fundamentals: Understanding of large language models, their inner workings, capabilities, and limitations
  • AI Engineering Techniques: Knowledge of prompt engineering, context engineering, AI agent patterns (RAG, text-to-sql, etx)
  • AI Frameworks: Hands-on experience with at least one framework: LangChain,

LangGraph, CrewAI, or similar

  • Vector Databases: Familiarity with vector stores (Pinecone, Weaviate, ChromaDB, FAISS, etc.) for embeddings and retrieval
  • Software Development: Understanding of Git workflows, version control with GitHub, and software development best practices
  • Collaboration: Experience working in Agile/Scrum teams with sprint-based development
  • Strong problem-solving skills and ability to learn new technologies quickly
  • Exposure to AI-assisted development tooling (e.g. GitHub CoPilot, Claude Code, Cursor, or equivalent)

· Experience with MCP (Model Context Protocol) or similar tool integration/orchestration frameworks

· Strong understanding of AI system security, including:

o Prompt injection risks

o Data leakage prevention

o Access control (RBAC/ABAC) for tools and data

· Experience building secure, enterprise-grade AI solutions with governance and compliance considerations

Nice to have

· Experience with enterprise AI platforms, multi-agent systems, or internal tool ecosystems

· Familiarity with auditability, observability, and evaluation frameworks for LLMs

We are proud to offer a range of incentives to our employees worldwide. These benefits are available to everyone, regardless of grade, and reflect the values we stand for:

Flexibility: Enjoy unlimited vacation, subject to local regulations and business priorities. Benefit from hybrid working arrangements and inclusive policies such as paid time off for voting, bereavement, and sick leave.

Well-being: Access confidential one-to-one support through our Employee Assistance Program, connect with our network of Wellbeing Champions and Gather Groups, and take part in monthly events and initiatives designed to help you thrive-inside and outside of work.

Health & Financial Security: Medical, life and disability insurance, retirement plans, lifestyle, and other benefits.*

Sustainability: Paid time off for volunteering and donation-matching opportunities to support causes that matter to you.

Inclusion: Get involved in our inclusion communities, such as Count Me In, Culture@Finastra, Proud@Finastra, Disabilities@Finastra, and Women@Finastra-open to everyone who wants to participate and contribute.

Career Development: Access online learning and accredited courses through our Skills & Career Navigator tool.

Recognition: Take part in our global recognition program, Finastra Celebrates, and share your voice through regular employee surveys that help shape our culture and ways of working.

*Specific benefits may vary by location.

At Finastra, each individual is unique-bringing their own ideas, perspectives, cultural backgrounds, and experiences. We learn from one another, value what makes us different, and create an environment where everyone feels included, supported, and able to be their authentic selves.

Be unique. Be exceptional. Help us make a difference at Finastra.

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