Senior AI Engineer

Karbon Business; Bengaluru; Hybrid; INR 2,000,000 - 3,000,000; Full time

Benefits offered by this job

Upskilling Policy

Team Outings

Flexible Work-from-Home

Menstrual WFH

Mobility Benefits

Parental Support

Job summary

Karbon Business is looking for a Senior AI Engineer to lead development and improvement of AI systems across its platform in Bengaluru. You will own AI models, focusing on production-grade applications and multi-agent systems.

The ideal candidate has 7+ years of experience in AI/ML, strong skills in Python, and a proven record of scaling AI products. Benefits include flexible working, upskilling opportunities, and team outings.

Qualifications

• 7+ years of experience in AI/ML, Machine Learning Engineering, Applied AI, or related roles.
• Proven experience building and shipping AI products into production at scale.
• Experience owning AI systems end-to-end.

Responsibilities

• Own the complete lifecycle of AI models from experimentation to production deployment.
• Drive new AI initiatives from concept to production.
• Optimize AI systems for performance, reliability, and cost efficiency.

Skills

AI/ML

Python programming

LLM APIs

MLOps

Software engineering fundamentals

Tools

LangGraph

SQL

JSON

Job description

AI Accountant (AiA) is building an AI-native platform transforming accounting and bookkeeping workflows. We simplify compliance, automate financial operations, and help businesses operate with clarity and confidence.

Backed by global investors like Y Combinator, we are scaling fast and building a team that combines speed, ownership, and sharp execution.

We’re not building a feature company. We’re building a category.

Our Mission & Vision

Mission: Simplify and automate financial workflows using AI to empower modern businesses.

Vision: Become the most trusted AI-driven financial operating system globally.

Job Summary

We are looking for a highly skilled Senior AI Engineer to lead the development, evaluation, deployment, and continuous improvement of AI systems across our product ecosystem. This role will own AI models and new AI initiatives end-to-end, with a strong focus on production-grade LLM applications, multi-agent systems, automation workflows, and model lifecycle management.

The ideal candidate combines deep expertise in modern AI/LLM technologies with strong software engineering fundamentals and experience scaling AI systems in production environments.

Requirements

Experience

• 7+ years of experience in AI/ML, Machine Learning Engineering, Applied AI, or related roles.
• Proven experience building and shipping AI products into production at scale.
• Experience owning AI systems end-to-end, from design through deployment and monitoring.

Technical Skills

• Strong Python programming skills and solid software engineering fundamentals.
• Hands-on experience with LLM APIs, Agentic Systems, LangGraph, RAG, MCP, and LLM Evaluation frameworks.
• Experience designing deterministic and semi-deterministic testing frameworks for AI systems and workflows.
• Strong knowledge of traditional Machine Learning models, data analysis, debugging, SQL, APIs, JSON, and workflow observability.
• Experience with LLMOps/MLOps practices, including model deployment, monitoring, evaluation, and lifecycle management.

Key Responsibilities

AI Model Ownership

• Own the complete lifecycle of AI models from experimentation to production deployment, monitoring, evaluation, and optimization.
• Improve existing AI systems by enhancing accuracy, reliability, latency, and scalability.
• Drive new AI initiatives from concept to production, collaborating closely with product, engineering, and business teams.

LLM & Agentic Systems Development

• Design, build, and optimize LLM-powered applications and agent-based workflows. Develop (RAG) pipelines and knowledge retrieval systems.
• Build robust orchestration frameworks using LangGraph and related agent frameworks.

Evaluation & Quality Engineering

• Design deterministic and semi-deterministic evaluation frameworks for LLMs and agent systems.
• Build automated testing frameworks for prompts, workflows, agents, and model outputs. Analyze model failures and implement improvements through structured evaluation cycles.

MLOps / LLMOps

• Develop and maintain scalable LLMOps infrastructure and workflows. Implement monitoring, observability, experimentation, versioning, and deployment processes.
• Optimize AI systems for performance, reliability, and cost efficiency.
• Drive best practices around model governance, testing, and release management.

What Success Looks Like in this role

• AI models consistently meet defined quality, latency, and reliability benchmarks.
• New AI initiatives are delivered from concept to production with measurable business impact.
• Robust evaluation and testing frameworks are established across AI systems.
• Production AI systems scale efficiently while maintaining performance and cost effectiveness.
• Accounting and finance automation capabilities are significantly enhanced through AI innovation.

Benefits

Our Way of Life — The AiA Values

• C - Collaborate to Win. We win together, not alone. We listen, challenge with care, and move as one team. Speed and success come from trust and cross-functional teamwork.
• E - Elevate the Bar. "Good enough" isn't good enough at AiA. We push for world-class in everything we do. We learn fast, aim high, and turn feedback into fuel.
• O - Own It End-to-End. We think like founders. We take full responsibility for outcomes—not just tasks. When things go wrong, we fix. No blame, no excuses—just impact.

Perks & Benefits

• Upskilling Policy – Access to tools, courses, and resources to stay ahead in content and AI workflows.
• Team Outings – Offsites and outings to celebrate wins and build stronger bonds.
• Flexible Work-from-Home – Up to 12 days remote every 6 months.
• Menstrual WFH – Up to 3 days per month.
• Mobility Benefits – Relocation and travel support.
• Parental Support – Maternity, paternity, and adoption leave.