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Salary
≈ $56k – $148k per year (Estimated)
Location
Hybrid (Bengaluru, India)
Seniority
Architect · 6+ years exp

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 15, 2026. Sage scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Sage is a British software company headquartered in Newcastle upon Tyne that makes accounting, financial management, payroll and HR software for small and medium-sized businesses, including Sage Intacct, Sage X3 and Sage Accounting. Founded in 1981 and listed on the London Stock Exchange as The Sage Group plc, it serves customers through offices across the UK, Europe, North America, Africa and Asia-Pacific, with large teams in Atlanta, Paris, Frankfurt, Toronto and Barcelona. It hires sales development and account managers, partner enablement and product support specialists, marketing, SEO and data analysts, and finance and compensation staff.
Backed by Pear VC
AI Infrastructure Engineer (Mid / Senior)

Location: Bengaluru (Hybrid - 3 days a week in office)

About Us

Sage is a global leader in accounting and business management software, trusted by millions of businesses worldwide. Together with our Bengaluru engineering team, we are building finance, accounting, payroll and expense management solutions that simplifies how businesses track and reconcile spending.

Thousands of finance teams globally use our product to streamline expense management, integrate seamlessly with leading accounting platforms, and are recognized for its clean design, usability, and speed.

We're investing heavily in AI - building the platform that lets AI agents and assistants do real engineering work, reliably and at scale. This team designs and runs the infrastructure behind our coding agents, review agents, and internal AI assistants: the orchestration, context and memory systems, evaluation frameworks, and feedback loops that make them better over time.

What We're Looking For

We're looking for someone with 3+ years of software engineering experience (mid-level) or 6+ years (senior), with hands-on experience building LLM-powered or agent-based systems in production.

Technical Skills

  • Solid software engineering fundamentals: system design, API design, data modelling, and clean, maintainable code.
  • Experience building and running production systems in the cloud (AWS, GCP, or Azure), including containers, Kubernetes or similar, and infrastructure as code.
  • Hands-on experience with distributed systems: queues, async workflows, concurrency, reliability, and failure handling.
  • Practical experience building with LLMs: tool use, agents, prompt and context engineering, RAG, and evaluation.
  • Familiarity with agent protocols and ecosystems (e.g., MCP) and with using AI coding tools day to day.

Leadership & Ownership

  • Comfort working independently and handling ambiguity: you can take a loosely defined problem, scope it, and drive it to production.
  • Clear written and verbal communication, including explaining trade-offs to both technical and non technical audiences.
  • At the senior level, we also expect you to lead projects and set technical direction, mentor other engineers, define evaluation and quality standards, and influence architecture across teams.

Mindset & Collaboration

  • Growth mindset - curious, always learning, and open to feedback.
  • Works closely with the engineers who use these tools every day; you help the whole organization build software better and faster.

Nice to Have

  • Experience with trace analysis or log mining to find and fix agent failure modes.
  • Experience building internal platforms or SDKs that other teams adopted.
  • Background in observability, CI/CD, or developer productivity tooling.
  • Experience with model routing, cost optimization, or prompt caching.
  • Open-source or public contributions in agent tooling or LLM infrastructure.

What to Expect

  • We value humility and collaboration - we're looking for people who can work as part of a team, not in silos.
  • We expect engineers to take ownership beyond just writing code - including tests, documentation, and long-term system quality.
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